Elevator call allocation with adaptive multi-objective optimization

Abstract

Apparatuses, methods, and computer programs for elevator call allocation with adaptive multi-objective optimization are disclosed. At least some of the disclosed embodiments may allow the objective function to be adaptively and smoothly changed according to passenger traffic. This, in turn, may allow for a minimum latency in all traffic situations compared to using a fixed objective function. Further, at least some of the disclosed embodiments may allow for adaptively and smoothly changing the objective function according to traffic while taking into account user preferences via a single transit time objective parameter.

Description

Technical Field

[0001] The present disclosure relates to the field of elevators, and more particularly, to elevator call allocation with adaptive multi-objective optimization. Background Art

[0002] In a conventional elevator control with up and down call buttons, a group of elevators can be controlled, for example, so that the average call time is as short as possible.

[0003] In a destination control system, the call giving device may be equipped with a keyboard or a touch screen, and passengers command an elevator ride by giving their destination floor on the call giving device. In addition to the waiting time, this additional destination floor information allows the elevator group controller to consider and optimize other objectives related to the passenger service level, such as arrival time at the destination, how long the passenger journey takes in total, including the waiting time at the arrival floor, and the transit time in the serving elevator to the moment the passenger leaves the elevator at the destination floor.

[0004] Traditionally, the goal of an elevator group controller is to control the elevator group so that the average waiting time for passengers is as short as possible. However, since the elevator group controller cannot see passengers that will arrive in the future, strictly minimizing the waiting time of existing passengers in call allocation may not always be the best way to minimize the actual waiting time for all passengers. Especially during heavy traffic in a destination control system, a pure arrival time to destination target may result in shorter waits than a pure waiting time target, since the arrival time to destination target may provide greater processing power. For example, for lighter traffic, a group controller with a waiting time target may saturate faster than a group controller with an arrival time to destination target. Summary of the invention

[0005] This summary is provided to introduce some concepts in a simplified form, which are further described in the detailed description below. This summary is not intended to identify key features or essential features of the claimed subject matter, nor is it intended to be used to limit the scope of the claimed subject matter.

[0006] The object of the present disclosure is to allow elevator call allocation with adaptive multi-objective optimization. The aforementioned and other objects are achieved by the features of the independent claims. Further implementation forms are evident from the dependent claims, the description and the drawings.

[0007] According to a first aspect of the present disclosure, a device for allocating elevator calls in an elevator group of an elevator system is provided. The device includes at least one processor and at least one memory including computer program code. The at least one memory and the computer program code are configured to, together with the at least one processor, cause the device to at least execute obtaining at least one current passenger traffic index related to the elevator group. The at least one memory and the computer program code are further configured to, together with the at least one processor, cause the device to at least execute: determining a weight of each of at least two passenger traffic optimization objectives of a passenger traffic objective function based on the obtained at least one current passenger traffic index. The at least one memory and the computer program code are also configured to, together with the at least one processor, cause the device to at least execute: optimizing the passenger traffic objective function using the determined weights. The at least one memory and the computer program code are also configured to, together with the at least one processor, cause the device to at least execute: allocating subsequent elevator calls to elevator cars in the elevator group based on the result of optimizing the passenger traffic objective function.

[0008] In an implementation of the first aspect, the at least two passenger traffic optimization objectives include waiting time and at least one additional passenger traffic optimization objective.

[0009] In an implementation form of the first aspect, the weight of the at least one additional passenger traffic optimization objective comprises: 1-ω, where ω represents the weight of the waiting time.

[0010] In an implementation of the first aspect, at least one additional passenger traffic optimization objective includes at least a time to arrive at a destination.

[0011] In an implementation of the first aspect, at least one current passenger traffic indicator includes a current average waiting time AWT i and the current elevator car load factor CLF i Obtaining the at least one current passenger traffic index comprises determining at least TTD_j term and The call allocation on the passengers of TTD_k items is minimized, where i represents the elevator call allocation instance, represents the weight of the entrance floor e, represents the weight of non-entrance floor p, WT represents waiting time, and TTD represents time to destination. Obtaining at least one current passenger traffic index also includes determining an average waiting time and an elevator car load factor based on the determined call allocation minimization sum.

[0012] In an implementation of the first aspect, at least one memory and the computer program code are further configured to, together with the at least one processor, cause the apparatus to at least perform: determining a subsequent weight for an entrance floor and subsequent weights for non-entrance floors The at least one memory and the computer program code are further configured to, with the at least one processor, cause the apparatus to at least perform: determining updated weights for entrance floors and non-entrance floors to be used in the subsequent elevator call allocation using exponential smoothing:

[0013]

[0014] where δ represents a parameter that determines how slowly the weights change.

[0015] In an implementation form of the first aspect, determining a weight for each of the at least two passenger traffic optimization objectives of the passenger traffic objective function comprises determining a weight for a waiting time of a passenger from an entrance floor based on a current average waiting time and a current elevator car load factor using a first sigmoid function:

[0016]

[0017] Determining a weight for each of the at least two passenger traffic optimization objectives of the passenger traffic objective function further includes determining a weight for a waiting time of passengers from non-entrance floors based on the current average waiting time using a second sigmoid function:

[0018]

[0019] where α, β, and γ represent parameters that specify the shape of the sigmoid function.

[0020] In an implementation of the first aspect, determining a weight for each of at least two passenger traffic optimization objectives of the passenger traffic objective function comprises: determining a weight for a waiting time of passengers from an entrance floor and a non-entrance floor based on a current average waiting time using a second sigmoid function:

[0021]

[0022] where α, β, and γ represent parameters that specify the shape of the sigmoid function.

[0023] In an implementation of the first aspect, the at least one additional passenger transportation optimization objective includes transit time.

[0024] In an implementation form of the first aspect, obtaining at least one current passenger traffic indicator includes determining at least one of an average transit time or an average transit time deviation following a current elevator call assignment.

[0025] In an implementation form of the first aspect, the at least one memory and the computer program code are further configured to, together with the at least one processor, cause the apparatus to at least perform: obtaining short-term statistics on the elevator calls served so as to determine at least one of an average transit time or an average transit time deviation.

[0026] In an implementation form of the first aspect, determining a weight for each of the at least two passenger traffic optimization objectives of the passenger traffic objective function comprises obtaining a weight for a waiting time of a subsequent elevator call assignment as a correction for a difference between a destination transit time deviation and a determined average transit time deviation or a difference between a destination transit time and a determined average transit time.

[0027] In an implementation of the first aspect, at least one memory and the computer program code are further configured to, with the at least one processor, cause the apparatus to obtain the correction from a controller.

[0028] In an implementation form of the first aspect, the controller comprises a proportional-integral-derivative (PID) controller or a proportional-integral (PI) controller.

[0029] In an implementation of the first aspect, the passenger traffic objective function includes:

[0030] ω*WT+(1-ω)*TT, or

[0031] ω*WT+(1-ω)*TTD,

[0032] Where WT represents the sum of waiting time, TT represents the sum of transportation time, TTD represents the sum of arrival time at the destination, and ω represents the weight of the waiting time obtained for the subsequent elevator call allocation.

[0033] In an implementation of the first aspect, the at least one additional passenger transportation optimization objective further includes at least one of time to destination or transit time and energy consumption.

[0034] In an implementation of the first aspect, at least one current passenger traffic indicator includes at least a current average waiting time associated with a first controller configured to provide a first control signal and at least one of a current average transit time or a current average transit time deviation associated with a second controller configured to provide a second control signal. Determining a weight for each of at least two passenger traffic optimization objectives of the passenger traffic objective function includes determining a weight for each of the at least two passenger traffic optimization objectives based on the first control signal and the second control signal.

[0035] According to a second aspect of the present disclosure, there is provided an apparatus for allocating elevator calls in an elevator group of an elevator system. The apparatus includes a device for performing the step of obtaining at least one current passenger traffic index associated with the elevator group. The device is further configured to determine a weight for each of at least two passenger traffic optimization objectives of a passenger traffic objective function based on the obtained at least one current passenger traffic index. The device is further configured to perform an optimization of the passenger traffic objective function using the determined weights. The device is further configured to perform the step of allocating subsequent elevator calls to elevator cars in the elevator group based on the result of optimizing the passenger traffic objective function.

[0036] In an implementation of the first aspect, the at least two passenger traffic optimization objectives include waiting time and at least one additional passenger traffic optimization objective.

[0037] In an implementation of the second aspect, the weight of at least one additional passenger traffic optimization objective includes: 1-ω, where ω represents the weight of the waiting time.

[0038] In an implementation of the second aspect, at least one additional passenger traffic optimization objective includes at least a time to arrive at a destination.

[0039] In an implementation of the second aspect, at least one current passenger traffic indicator includes a current average waiting time AWT i and the current elevator car load factor CLF i Obtaining at least one current passenger traffic index includes determining at least TTD_j term and The call allocation on the passengers of TTD_k items is minimized, where i represents the elevator call allocation instance, represents the weight of the entrance floor e, represents the weight of non-entrance floor p, WT represents waiting time, and TTD represents time to destination. Obtaining at least one current passenger traffic index also includes determining an average waiting time and an elevator car load factor based on the determined call allocation minimization sum.

[0040] In an implementation of the second aspect, the device is further configured to: determine a subsequent weight for the entrance floor and subsequent weights for non-entrance floors The device is also configured to use exponential smoothing to perform the determination of updated weights for entrance floors and non-entrance floors to be used in subsequent elevator call assignments:

[0041]

[0042] where δ represents a parameter that determines how slowly the weights change.

[0043] In an implementation form of the second aspect, determining a weight for each of the at least two passenger traffic optimization objectives of the passenger traffic objective function comprises determining a weight for a waiting time of a passenger from an entrance floor based on a current average waiting time and a current elevator car load factor using a first sigmoid function:

[0044]

[0045] Determining a weight for each of the at least two passenger traffic optimization objectives of the passenger traffic objective function further includes determining a weight for a waiting time of passengers from non-entrance floors based on the current average waiting time using a second sigmoid function:

[0046]

[0047] where α, β, and γ represent parameters that specify the shape of the sigmoid function.

[0048] In an implementation of the second aspect, determining the weight of each of the at least two passenger traffic optimization objectives of the passenger traffic objective function comprises: using a second sigmoid function, based on the current average waiting time, determining the weight of the waiting time of passengers from the entrance floor and the non-entrance floor:

[0049]

[0050] where α, β, and γ represent parameters that specify the shape of the sigmoid function.

[0051] In an implementation of the second aspect, at least one additional passenger transportation optimization objective includes transit time.

[0052] In an implementation of the second aspect, obtaining at least one current passenger traffic indicator includes determining at least one of an average transit time or an average transit time deviation following a current elevator call assignment.

[0053] In an implementation form of the second aspect, the device is further configured to perform obtaining short-term statistics on serviced elevator calls to facilitate determining at least one of an average transit time or an average transit time deviation.

[0054] In an implementation form of the second aspect, determining a weight for each of the at least two passenger traffic optimization objectives of the passenger traffic objective function comprises obtaining a weight for a waiting time of a subsequent elevator call assignment as a correction for a difference between a destination transit time deviation and a determined average transit time deviation or a difference between a destination transit time and a determined average transit time.

[0055] In an implementation of the second aspect, the device is further configured to perform obtaining the correction from a controller.

[0056] In an implementation form of the second aspect, the controller comprises a proportional-integral-derivative (PID) controller or a proportional-integral (PI) controller.

[0057] In an implementation of the second aspect, the passenger traffic objective function includes:

[0058] ω*WT+(1-ω)*TT, or

[0059] ω*WT+(1-ω)*TTD,

[0060] Where WT represents the sum of waiting time, TT represents the sum of transportation time, TTD represents the sum of arrival time at the destination, and ω represents the weight of the waiting time obtained for the subsequent elevator call allocation.

[0061] In an implementation of the second aspect, the at least one additional passenger traffic optimization objective further includes at least one of arrival time at a destination or transportation time and energy consumption.

[0062] In an implementation of the second aspect, at least one current passenger traffic indicator includes at least a current average waiting time associated with a first controller configured to provide a first control signal and at least one of a current average transit time or a current average transit time deviation associated with a second controller configured to provide a second control signal. Determining a weight for each of at least two passenger traffic optimization objectives of the passenger traffic objective function includes determining a weight for each of the at least two passenger traffic optimization objectives based on the first control signal and the second control signal.

[0063] According to a third aspect of the present disclosure, a method is provided. The method includes obtaining at least one current passenger traffic index related to the elevator group by a device for elevator call allocation in an elevator group of an elevator system. The method further includes determining, by the device, a weight of each of at least two passenger traffic optimization objectives of a passenger traffic objective function based on the obtained at least one current passenger traffic index. The method also includes optimizing the passenger traffic objective function by the device using the determined weights. The method also includes allocating subsequent elevator calls to elevator cars in the elevator group by the device based on the result of optimizing the passenger traffic objective function.

[0064] In an implementation of the first aspect, the at least two passenger traffic optimization objectives include waiting time and at least one additional passenger traffic optimization objective.

[0065] In an implementation of the third aspect, the weight of at least one additional passenger traffic optimization objective includes 1-ω, where ω represents the weight of the waiting time.

[0066] In an implementation of the third aspect, at least one additional passenger traffic optimization objective includes at least a time to arrive at a destination.

[0067] In an implementation of the third aspect, at least one current passenger traffic indicator includes a current average waiting time AWT i and the current elevator car load factor CLF i Obtaining at least one current passenger traffic index includes determining at least TTD_j term and The call allocation on the passengers of TTD_k items is minimized, where i represents the elevator call allocation instance, represents the weight of the entrance floor e, represents the weight of non-entrance floor p, WT represents waiting time, and TTD represents time to destination. Obtaining at least one current passenger traffic index also includes determining an average waiting time and an elevator car load factor based on the determined call allocation minimization sum.

[0068] In an implementation of the third aspect, the method further includes: determining a subsequent weight for the entrance floor and subsequent weights for non-entrance floors The method also includes using exponential smoothing to determine updated weights for entrance floors and non-entrance floors to be used in subsequent elevator call assignments:

[0069]

[0070] where δ represents a parameter that determines how slowly the weights change.

[0071] In an implementation form of the third aspect, determining a weight for each of the at least two passenger traffic optimization objectives of the passenger traffic objective function comprises determining a weight for a waiting time of a passenger from an entrance floor based on a current average waiting time and a current elevator car load factor using a first sigmoid function:

[0072]

[0073] Determining a weight for each of the at least two passenger traffic optimization objectives of the passenger traffic objective function further includes determining a weight for a waiting time of passengers from non-entrance floors based on the current average waiting time using a second sigmoid function:

[0074]

[0075] where α, β, and γ represent parameters that specify the shape of the sigmoid function.

[0076] In an implementation of the third aspect, determining the weight of each of the at least two passenger traffic optimization objectives of the passenger traffic objective function comprises: using a second sigmoid function, based on the current average waiting time, determining the weights of the waiting times of passengers from the entrance floor and the non-entrance floor:

[0077]

[0078] where α, β, and γ represent parameters that specify the shape of the sigmoid function.

[0079] In an implementation of the third aspect, the at least one additional passenger transportation optimization objective includes transit time.

[0080] In an implementation of the third aspect, obtaining at least one current passenger traffic indicator includes determining at least one of an average transit time or an average transit time deviation after a current elevator call assignment.

[0081] In an implementation form of the third aspect, the method further comprises obtaining short-term statistics on serviced elevator calls to facilitate determining at least one of an average transit time or an average transit time deviation.

[0082] In an implementation form of the third aspect, determining a weight for each of the at least two passenger traffic optimization objectives of the passenger traffic objective function comprises obtaining a weight for a waiting time of a subsequent elevator call assignment as a correction for a difference between a destination transit time deviation and a determined average transit time deviation or a difference between a destination transit time and a determined average transit time.

[0083] In an implementation form of the third aspect, the method further comprises performing obtaining the correction from a controller.

[0084] In an implementation form of the third aspect, the controller includes a proportional-integral-derivative (PID) controller or a proportional-integral (PI) controller.

[0085] In an implementation of the third aspect, the passenger traffic objective function includes:

[0086] ω*WT+(1-ω)*TT, or

[0087] ω*WT+(1-ω)*TTD,

[0088] Where WT represents the sum of waiting time, TT represents the sum of travel time, TTD represents the sum of time to destination, and ω represents the weight of the waiting time obtained for subsequent elevator call allocations.

[0089] In an implementation of the third aspect, at least one additional passenger traffic optimization objective further includes at least one of arrival time at a destination or transportation time and energy consumption.

[0090] In an implementation of the third aspect, at least one current passenger traffic indicator includes at least a current average waiting time associated with a first controller configured to provide a first control signal and at least one of a current average transit time or a current average transit time deviation associated with a second controller configured to provide a second control signal. Determining a weight for each of at least two passenger traffic optimization objectives of the passenger traffic objective function includes determining a weight for each of the at least two passenger traffic optimization objectives based on the first control signal and the second control signal.

[0091] According to a fourth aspect of the present disclosure, a computer program is provided. The computer program includes instructions for causing an apparatus for distributing elevator calls in an elevator group of an elevator system to perform at least the following operations: obtaining at least one current passenger traffic index related to the elevator group; determining a weight of each of at least two passenger traffic optimization objectives of a passenger traffic objective function based on the obtained at least one current passenger traffic index, the at least two passenger traffic optimization objectives including waiting time and at least one additional passenger traffic optimization objective; optimizing the passenger traffic objective function using the determined weights; and distributing subsequent elevator calls to elevator cars in the elevator group based on the result of optimizing the passenger traffic objective function.

[0092] At least some of the disclosed embodiments may allow adaptively and smoothly changing the objective function according to passenger traffic. This in turn may allow minimizing waiting times in all traffic situations compared to using a fixed objective function. At least some of the disclosed embodiments may allow adapting the objective function to passenger traffic without passenger counting.

[0093] At least some of the disclosed embodiments may allow adaptively and smoothly changing the objective function according to traffic while taking into account user preferences via a single transit time objective parameter. In addition, changing the transit time objective value or the transit time deviation objective value may allow for different passenger service levels.

[0094] By referring to the following detailed description considered in conjunction with the accompanying drawings, many of the features will be more readily appreciated as they become better understood. BRIEF DESCRIPTION OF THE DRAWINGS

[0095] In the following, example embodiments are described in more detail with reference to the accompanying drawings and figures, in which:

[0096] Figure 1 is a block diagram showing an elevator system;

[0097] Figure 2 is a block diagram illustrating an apparatus for elevator call distribution according to an embodiment of the present disclosure;

[0098] Figure 3 is a block diagram illustrating an apparatus for elevator call distribution with a feedback loop according to an embodiment of the present disclosure;

[0099] Figure 4 is a diagram illustrating a sigmoid function according to an embodiment of the present disclosure;

[0100] Figure 5 is a flow chart illustrating a method according to an embodiment of the present disclosure;

[0101] Figure 6 is a diagram showing the overall concept of an embodiment related to energy consumption; and

[0102] Figure 7 is a diagram showing an example of a weight controller for an energy consumption related embodiment.

[0103] In the following, identical reference numerals refer to identical or at least functionally equivalent features. DETAILED DESCRIPTION

[0104] In the following description, reference is made to the accompanying drawings, which form a part of the present disclosure and in which are shown by way of illustration specific aspects in which the present invention may be placed. It should be understood that other aspects may be utilized and structural or logical changes may be made without departing from the scope of the present invention. Therefore, the following detailed description should not be considered to have a limiting meaning, as the scope of the present invention is defined in the appended claims.

[0105] For example, it should be understood that the disclosure in conjunction with the described method may also apply to a corresponding device or system configured to perform the method, and vice versa. For example, if a specific method step is described, the corresponding device may include a unit that performs the described method step, even if such a unit is not explicitly described or shown in the drawings. On the other hand, for example, if a specific device or equipment is described based on a functional unit, the corresponding method may include steps to perform the described function, even if such steps are not explicitly described or shown in the drawings. In addition, it should be understood that the features of the various example aspects described herein may be combined with each other unless otherwise specifically noted.

[0106] The present disclosure relates to elevator call allocation with adaptive multi-objective optimization.

[0107] Figure 1 1 is a block diagram illustrating an elevator system 100. The elevator system 100 includes a group of elevator cars 131-133 controlled by respective elevator controllers 121-123. Each elevator controller 121-123 is connected to an elevator group controller 110. The elevator system 100 may include a destination-based control system and / or a conventional (non-destination-based) control system.

[0108] At least some of the disclosed embodiments may allow for controlling an elevator group so that the waiting time and arrival time at destination (and / or transit time and / or transit time deviation) of passenger objectives are optimized simultaneously so that their weights (describing their relative importance) change adaptively and smoothly depending on the traffic. For example, the waiting time objective may be minimized during light passenger traffic, and as passenger traffic increases, the weight of the arrival time at destination (and / or transit time and / or transit time deviation) objective may be smoothly increased, and when passenger traffic is close to or above the handling capacity of the elevator group, the focus may be primarily on minimizing the arrival time at destination (and / or transit time and / or transit time deviation) objective.

[0109] In other words, at least some of the disclosed embodiments may allow for the objective function to be adjusted based on passenger traffic conditions.

[0110] At least some of the disclosed embodiments may allow for transforming the waiting time and arrival time at destination (and / or transit time and / or transit time deviation) objectives into a single objective problem by using a weighted sum approach. However, the present disclosure is not limited to this particular scaling approach. Instead, any A family of parameterized value functions: (where ω∈[0,1] controls the relative importance of arrival time at destination (and / or transit time and / or transit time deviation) compared to waiting time).

[0111] At least some of the disclosed embodiments may allow for adjustment of weights of objectives without requiring traffic predictions based on passenger counts.

[0112] At least some of the disclosed embodiments may allow a control loop mechanism (e.g., in an elevator group controller) to adjust the target weights between call allocations based on the difference between the desired target level of transit time deviation and the measured transit time deviation or the difference between the desired target level of transit time and the measured transit time. This approach may allow different service level profiles to be provided. For example, if the transit time goal or the transit time deviation goal is set to zero, the device 200 may optimize the transit time or the transit time deviation or the time to destination under all traffic conditions, while for large transit time goal values ​​or large transit time deviation goal values, the device 200 may optimize the waiting time, and for small values, the objective function may change, for example, based on passenger traffic.

[0113] At least some of the disclosed embodiments may allow for providing building / facility managers with an easy and understandable way (with only one parameter) to adjust passenger service levels according to their preferences.

[0114] At least some of the disclosed embodiments may allow for implementation of an objective function such that during light traffic, user preferences may be considered and optimized, but during heavy traffic, the focus may be on maximizing processing capacity independent of user preferences.

[0115] At least some of the disclosed embodiments may allow for reduced energy consumption while still allowing at least adequate performance.

[0116] At least some of the disclosed embodiments may allow for saving operating energy at least as much as shutting down elevators or placing elevators in standby mode, while still keeping all elevators available to passengers and being able to react to sudden changes in passenger demand. In addition, at least some of the disclosed embodiments may not require additional intelligence to detect off-peak hours to shut down elevators. At least some of the disclosed embodiments may further allow for reducing the distance that elevators travel, and therefore reducing wear and tear on equipment.

[0117] At least some of the disclosed embodiments may also operate in a destination control system and may allow for consideration of at least two different service level objectives.

[0118] At least some of the disclosed embodiments may operate without the need for traffic estimation.

[0119] At least some of the disclosed embodiments may allow for consideration of preferences of stakeholders, such as building managers, by, for example, adjusting target levels for average wait time and average transit time deviation.

[0120] It should be noted that the time to destination is the sum of the waiting time and the transport time. Therefore, the waiting time target and the time to destination target are related. Therefore, in some embodiments, a transport time (or transport time deviation) target can be used instead of the time to destination target.

[0121] Next, based on Figure 2 An exemplary embodiment of an apparatus 200 for elevator call distribution in an elevator group of an elevator system is described. Some features of the described unit are optional features which may provide further advantages.

[0122] Figure 2 is a block diagram illustrating an apparatus 200 for distributing elevator calls in an elevator group of an elevator system according to an example embodiment. In at least some embodiments, the elevator system may include Figure 1 An elevator system 100 is provided.

[0123] The apparatus 200 includes at least one processor or processing unit 202, and at least one memory 204 including computer program code and coupled to the at least one processor 202, which can be used to implement the functions described in more detail later. The apparatus 200 may also include Figure 2 Other elements not shown.

[0124] In an example embodiment, the apparatus 200 may be at least partially included in an elevator group controller that controls a plurality of elevator cars, such as in Figure 1 In another example embodiment, the device 200 may be at least partially included in a cloud-based service, and at least some remaining portions of the device 200 may be included in the elevator group controller 110.

[0125] Although the device 200 is depicted as including only one processor 202, the device 200 may include more processors. In an embodiment, the memory 204 is capable of storing instructions, such as an operating system and / or various applications. In addition, the memory 204 may include a storage device that can be used to store at least some of the information and data used in the disclosed embodiments, for example.

[0126] In addition, the processor 202 is capable of executing the stored instructions. In an embodiment, the processor 202 may be embodied as a multi-core processor, a single-core processor, or a combination of one or more multi-core processors and one or more single-core processors. For example, the processor 202 may be embodied as one or more of various processing devices, such as a coprocessor, a microprocessor, a controller, a digital signal processor (DSP), a processing circuit with or without an accompanying DSP, or various other processing devices including integrated circuits, such as, for example, application specific integrated circuits (ASICs), field programmable gate arrays (FPGAs), microcontroller units (MCUs), hardware accelerators, special-purpose computer chips, etc. In an embodiment, the processor 202 may be configured to perform hard-coded functions. In an embodiment, the processor 202 is implemented as an executor of software instructions, wherein the instructions may specifically configure the processor 202 to perform the algorithms and / or operations described herein when the instructions are executed.

[0127] At least one memory 204 may be embodied as one or more volatile memory devices, one or more non-volatile memory devices, and / or a combination of one or more volatile memory devices and non-volatile memory devices. For example, at least one memory 204 may be embodied as a semiconductor memory (such as a mask ROM, a PROM (programmable ROM), an EPROM (erasable PROM), a flash ROM, a RAM (random access memory), etc.).

[0128] The at least one memory 204 and the computer program code are configured to, together with the at least one processor 202, cause the apparatus 200 to at least perform the step of obtaining at least one current passenger traffic index associated with the elevator group.

[0129] The at least one memory 204 and the computer program code are further configured to, together with the at least one processor 202, cause the apparatus 200 to at least perform: determining a weight of each of at least two passenger traffic optimization objectives of the passenger traffic objective function based on the obtained at least one current passenger traffic index. For example, the at least two passenger traffic optimization objectives may include waiting time and at least one additional passenger traffic optimization objective.

[0130] The at least one memory 204 and the computer program code are further configured to, with the at least one processor 202, cause the apparatus 200 to at least perform optimizing a passenger traffic objective function using the determined weights.

[0131] The at least one memory 204 and the computer program code are further configured to, together with the at least one processor 202, cause the apparatus 200 to at least perform: allocating subsequent elevator calls to the elevator cars 131, 132, 133 in the elevator group based on the optimization result of the passenger traffic objective function.

[0132] In at least some embodiments, the weight of at least one additional passenger traffic optimization objective may include 1-ω, where ω represents the weight of the waiting time. When there are more than one additional passenger traffic optimization objective, their sum may include 1-ω. In other words, a weighted summation method (or any other scalarization method in which the relative importance of the objectives is expressed by weights) may be utilized such that the weight (ω) of the waiting time objective used in the current elevator call allocation may be determined based on the results of the previous elevator call allocation, and the weight of the arrival time at the destination (or transit time) is 1-ω.

[0133] In a first implementation example, at least one additional passenger traffic optimization objective may include at least a time to destination. For example, the weights of the waiting time and time to destination objectives may be adjusted such that the focus is primarily on minimizing the weight of the waiting time objective during light passenger traffic, the weight of the time to destination objective increases as traffic intensity increases, and the focus is primarily on minimizing the weight of the time to destination objective when traffic approaches the handling capacity of the elevator group.

[0134] In addition, in the first implementation example, at least one current passenger traffic indicator may include a current average waiting time (AWT) i ) and the current elevator car load factor (CLF i ).

[0135] For example, separate weights may be maintained for elevator calls from an entrance floor (or floors) and elevator calls from other floors. In at least some embodiments, the average waiting time and elevator car load factor calculated in each assignment may be used as a proxy for the prevailing passenger traffic conditions to calculate new weights to be used in the next elevator call assignment.

[0136] Thus, obtaining at least one current passenger traffic indicator may include determining (in the i-th elevator call allocation) at least TTD_j term and The call allocation on the passengers of TTD_k items is minimized, where i represents the elevator call allocation instance, represents the weight of the entrance floor (e), represents the weight of the non-entrance floor (p), WT represents the waiting time, and TTD represents the time to reach the destination. For example, a genetic algorithm can be used for this. At least in some embodiments, the minimization sum can also have other terms, such as a penalty term.

[0137] Obtaining at least one current passenger traffic indicator may also include determining an average waiting time and an elevator car load factor based on the determined call distribution minimizing the sum.

[0138] In addition, in the first implementation example, at least one memory 204 and the computer program code may also be configured to, together with at least one processor 202, cause the apparatus 200 to at least perform determining a subsequent (or new) weight for the entrance floor. and subsequent (or new) weights for non-entrance floors Then, the at least one memory 204 and the computer program code may also be configured to, together with the at least one processor 202, cause the apparatus 200 to at least perform the following steps of determining updated weights of entrance floors and non-entrance floors to be used in subsequent elevator call allocations using exponential smoothing, for example, as follows:

[0139]

[0140] where δ represents a parameter that determines how slowly the weight changes, i.e., how important the history is relative to the latest value. In at least some embodiments, the subsequent (or new) weights for the entrance floors are and subsequent weights for non-entrance floors Can have the same value.

[0141] In other words, weights updated using exponential smoothing may include weights set to a weighted average of the current weights and the proposed new weights.

[0142] Furthermore, in the first implementation example, determining the weight of each of the at least two passenger traffic optimization objectives of the passenger traffic objective function may include using a first sigmoid function based on the current average waiting time (i.e., the average waiting time AWT of the i-th elevator call assignment) i ) and the current elevator car load factor (i.e., the elevator car load factor CLF of the i-th elevator call assignment i ) to determine the weight of the waiting time of passengers from the entrance floor (after the i-th elevator call allocation):

[0143]

[0144] In addition, determining the weight of each of the at least two passenger traffic optimization objectives of the passenger traffic objective function may also include using a second sigmoid function based on the current average waiting time (i.e., the average waiting time AWT of the i-th elevator call assignment) i ) determines the weight of the waiting time of passengers from non-entrance floors (after the i-th elevator call allocation):

[0145]

[0146] Here, α, β and γ denote parameters which specify the shape of the (first and / or second) sigmoid function.

[0147] Alternatively, determining the weight of each of the at least two passenger traffic optimization objectives of the passenger traffic objective function may include determining the weight of the waiting time of passengers from the entrance floor and the non-entrance floor based on the current average waiting time using a second sigmoid function:

[0148]

[0149] where α, β, and γ represent parameters that specify the shape of the sigmoid function, as described above.

[0150] These parameters α, β and γ of the sigmoid function may be determined based on, for example, simulations, statistical methods or machine learning methods. Alternatively, the sigmoid shape may be replaced by a function learned from data.

[0151] Figure 4 Graph 400 shows an example S-shaped function (as a function of average waiting time) according to an embodiment of the present disclosure. Figure 4 In the example, α=0.2, β=40 and γ=0.75.

[0152] In a second implementation example, at least one additional passenger traffic optimization objective may include transit time (and / or implicitly transit time deviation). For example, the weights of the waiting time and transit time objectives may be adjusted so that the focus is primarily on minimizing the weight of the waiting time objective during light passenger traffic, the weight of the transit time objective increases as traffic intensity increases, and when traffic approaches the handling capacity of the elevator group, the focus is primarily on minimizing the time to destination objective. In the time to destination minimization, both waiting time and transit time may have the same weight, and thus a ω lower limit, such as 0.5, may be used.

[0153] In addition, in a second implementation example, obtaining at least one current passenger traffic indicator may include determining an average transit time and / or an average transit time deviation after the current elevator call allocation. In other words, at the end of the elevator call allocation, the average transit time deviation may be calculated. In this document, the term "transit time deviation" is used to refer to the normal transit time minus the ideal transit time, and the term "ideal transit time" is used to refer to the transit time without any stops between the starting floor and the destination floor of the elevator call. Using the transit time deviation instead of the normal transit time allows the same deviation to be used for low-rise buildings and high-rise buildings with fast floors. In addition, when the transit time deviation is used, the two targets are very close on the same scale, which means that there is no need to scale the targets to the [0-1] range.

[0154] Furthermore, in the second implementation example, the at least one memory 204 and the computer program code may be further configured to, together with the at least one processor 202, cause the apparatus 200 to at least perform the step of obtaining short-term statistics on serviced elevator calls in order to determine an average transit time and / or an average transit time deviation.

[0155] In other words, since the average transit time or average transit time deviation may vary from one allocation to another, in order to prevent the weight of the waiting time objective from changing too much, short-term statistics about the service calls may be provided to the apparatus 200 and used for the average transit time or average transit time deviation calculation (but not for the objective function). In the objective function, the normal transit time may be used.

[0156] Furthermore, in the second implementation example, determining the weight of each of the at least two passenger traffic optimization objectives of the passenger traffic objective function may include obtaining a weight of the waiting time of a subsequent elevator call assignment as a correction of the difference between the destination transit time deviation and the determined average transit time deviation or the difference between the destination transit time and the determined average transit time. For example, the controller 310 (such as a proportional-integral-derivative (PID) controller or a proportional-integral (PI) controller discussed in more detail below) may calculate the error as the difference between the desired destination value of the transit time deviation and the determined / measured (average) transit time deviation, and apply the correction via a new weight of the waiting time objective for the next assignment.

[0157] Furthermore, in the second implementation example, the at least one memory 204 and the computer program code may also be configured to, together with the at least one processor 202, cause the apparatus 200 to obtain corrections from the controller 310. When a call is serviced, short-term statistics may be recorded in the memory.

[0158] In other words, in order to take into account user preferences and provide controllability of passenger service levels, a feedback loop formed by the controller 310 may be used. In at least some embodiments, the controller 310 may be included in, for example, the device 200 or the elevator group controller 110 ( Figure 1 to Figure 2 Controller 310 may adjust the ω value based on the difference between the measured or determined (average) delivery time deviation and the destination delivery time deviation or the difference between the measured or determined (average) delivery time and the target delivery time. Here, the destination delivery time deviation represents a user preference.

[0159] Furthermore, in the second implementation example, the passenger traffic objective function used in elevator call allocation may include, for example:

[0160] ω*WT+(1-ω)*TT, or

[0161] ω*WT+(1-ω)*TTD,

[0162] Where WT represents the sum of waiting times, TT represents the sum of transit times, TTD represents the sum of arrival times at the destination, and ω represents the weight of the waiting time obtained for subsequent elevator call assignments. For example, the ω value may come from the PID controller 310, and the ω value may change from one elevator call assignment to another.

[0163] Figure 3 The diagram 300 shows the apparatus 200 for elevator call distribution with a PID controller 310, as described above.

[0164] Furthermore, in the second implementation example, different transit time target levels or transit time deviation objective levels may result in different service level profiles. Thus, the elevator system 100 may be configured with the aid of a transit time objective;

[0165] 1) Optimize the time to destination by setting the delivery time deviation goal or delivery time goal to zero;

[0166] 2) optimize waiting time by setting the delivery time deviation goal or delivery time goal to a larger value; or

[0167] 3) Optimize waiting time during light traffic and arrival time at destination during heavy traffic by setting the delivery time deviation objective or delivery time objective to a small value (e.g., to 20, although this depends on the building and elevator parameters).

[0168] In a third implementation example, at least one additional passenger traffic optimization objective may include a time to destination or a transit time and energy consumption. In addition, at least one current passenger traffic indicator may include at least a current average waiting time (AWT) associated with a first controller configured to provide a first control signal, and a current average transit time and / or a current average transit time deviation (ATTDev) associated with a second controller configured to provide a second control signal. Determining a weight for each of the at least two passenger traffic optimization objectives of the passenger traffic objective function may include determining a weight for each of the at least two passenger traffic optimization objectives based on the first control signal and the second control signal.

[0169] exist Figure 6 The overall concept of the third implementation example is shown in the chart 600 of .Similar to the first and second implementation examples, there may be a pre-configured purpose level defined for a passenger traffic indicator.Each call allocation 602 can be performed by optimizing an objective function, wherein the importance of the target can be determined by a weight coefficient or weight.The value calculated for the performance indicator in the selected allocation solution can be fed to a separate weight controller module 601.The weight controller module 601 may be configured to monitor the difference between the level and the purpose level calculated in the allocation 602.For example, weights may be defined for energy consumption, the waiting time for a destination call, the waiting time for a landing call, the transportation time for a destination call and / or the transportation time for a car call.

[0170] In a third implementation example, call allocation 602 may be triggered, for example, when a call is registered (immediate allocation) or at a specific frequency (continuous allocation). A genetic algorithm or other suitable optimization method may be used to minimize a loss function of a weighted sum of the following form:

[0171]

[0172] Among them, for the selected solution x:

[0173] DCSWT(x) represents the sum of the waiting times of passengers who give destination calls,

[0174] DCSTTT(x) represents the sum of the transit times of passengers given a destination call.

[0175] LDGWT(x) represents the total waiting time of passengers given landing call,

[0176] LDGTT(x) represents the sum of the transportation time of passengers giving landing calls ( / car calls), EC(x) represents the total energy consumption, and

[0177] Penalty(x) can contain other terms.

[0178] Weight vector Can contain weight coefficients that control the importance of the corresponding criterion in the loss function.

[0179] Alternatively, a family of loss functions of the following form can be used:

[0180] Lω(x)

[0181] :=f ω (DCSWT(x),DCSTT(x),LDGWT(x),LDGTT(x),EC(x),Penalty(x)),

[0182] The weight vector ω can control the relative importance of each objective.

[0183] The energy consumption EC(x) caused by a candidate allocation x can be calculated as, for example, the sum of the energy consumptions of the cycles in the candidate routes implied by the allocation. Alternative approaches for calculating cycle-specific energy consumption may include, for example:

[0184] - Distance travelled: easy to calculate without the need for elevator group specific energy models; and

[0185] - Operation energy consumption calculated based on a model of the elevator system as a function of distance and load, with or without variation of potential energy.

[0186] exist Figure 7 An example of a weight controller for the above energy consumption related embodiments is shown in diagram 700 of FIG.

[0187] The passenger traffic indicators (AWT, ATTDev) calculated in the call distribution 601 may be fed to the state estimators 701A, 701B which are configured to smooth the raw values ​​received from the distribution 601. Similar to the second implementation example, in addition to the calls currently in the system, these calls may also contain a short-term history of calls from, for example, the last 2 minutes.

[0188] The state estimates may in turn be fed to controllers 702A, 702B, which generate control signals u∈[0,1] where a high value of u indicates that more weight should be applied to the corresponding indicator / goal. In a conversion block 703, the control signals from the indicator-specific controllers 702A, 702B may be combined into weights used in the allocation 601.

[0189] The state estimators 701A, 701B may comprise, for example, an exponential smoother, where the new estimate is a weighted average of the current estimate and a new value obtained from the allocation:

[0190]

[0191] where α represents a parameter that controls how aggressively the estimators 701A, 701B react to new observations.

[0192] The controllers 702A, 702B may include, for example, a PI controller, i.e., at each weight update step, the control signal u may be calculated as follows WT ,For example:

[0193]

[0194] where ∈ represents the difference between the estimate and the target (the upper limit between the minimum and maximum values), k I ,k P denote the gains of the integrator and proportional term respectively, and represents the proportional and integral terms of the PI controller (with upper limits between 0 and 1, or other minimum / maximum values), and u WT represents the final WT control signal fed to the conversion block 703.

[0195] The conversion block 703 can convert the control signal u WT ,u TT is mapped to a weight ω. It can include, for example:

[0196]

[0197] in Represents the configuration parameters that define the relative weight between waiting and transportation for non-destination control system passengers.

[0198] Ignoring the LDG weight, the rationale for this transformation is that the arrival time at the destination as a proxy for processing capacity can have the highest priority, so that if the delivery time deviation is higher than the destination, the control signal u TT Close to 1, weight Close to 1, ω EC close to 0, corresponding to full time-to-destination optimization. If the transit time deviation goal is achieved without full TTD optimization (i.e., u TT <1), WT control signal u WT Can be used to decide the relative importance between waiting time and energy consumption. Landing calls may be handled slightly differently because the system may not be able to monitor the achieved waiting time and time to destination (this may not be visible to the user if TT improves at the expense of WT). Also, TTD may not be a good proxy for the processing capacity of LDG calls, so it may not be best to use full time to destination optimization in high traffic.

[0199] Figure 5 An example flow diagram of a method 500 according to an example embodiment is shown.

[0200] At operation 501, the apparatus 200 for elevator call distribution in an elevator group of the elevator system 100 obtains at least one current passenger traffic index associated with the elevator group.

[0201] In operation 502 , the apparatus 200 determines a weight of each of at least two passenger traffic optimization objectives of a passenger traffic objective function based on the obtained at least one current passenger traffic index.

[0202] In operation 503 , the device 200 optimizes the passenger traffic objective function using the determined weights.

[0203] In operation 504, the apparatus 200 allocates subsequent elevator calls to the elevator cars 131, 132, 133 in the elevator group based on the optimization result of the passenger traffic objective function.

[0204] Method 500 may be performed by Figure 2 The method 500 is performed by the device 200. Operations 501-504 may be performed, for example, by at least one processor 202 and at least one memory 204. Other features of the method 500 are directly generated by the functions and parameters of the device 200, and therefore are not repeated here. The method 500 may be performed by a computer program.

[0205] The apparatus 200 may include means for performing at least one method described herein. In an example, the means may include at least one processor 202 and at least one memory 204 including program code, the program code being configured to cause the apparatus 200 to perform the method when executed by the at least one processor 202.

[0206] The functions described herein may be performed at least in part by one or more computer program product components (such as software components). According to an embodiment, the device 200 may include a processor or processor circuit, such as a microcontroller, which is configured by program code to perform an embodiment of the described operations and functions when executed. Alternatively or additionally, the functions described herein may be performed at least in part by one or more hardware logic components. For example, but not limited to, illustrative types of hardware logic components that can be used include field programmable gate arrays (FPGAs), program application specific integrated circuits (ASICs), program application specific standard products (ASSPs), systems on chip (SOCs), complex programmable logic devices (CPLDs), and graphics processing units (GPUs).

[0207] Any range or device value given herein may be expanded or changed without losing the effect sought. In addition, unless explicitly not permitted, any embodiment may be combined with another embodiment.

[0208] Although the subject matter has been described in language specific to structural features and / or actions, it should be understood that the subject matter defined in the appended claims is not necessarily limited to the specific features or actions described above. Instead, the specific features and actions described above are disclosed as examples of implementing the claims, and other equivalent features and actions are intended to fall within the scope of the claims.

[0209] It should be understood that the above benefits and advantages may relate to one embodiment or may relate to several embodiments. The embodiments are not limited to those embodiments that solve any or all of the problems described or those embodiments that have any or all of the benefits and advantages described. It will be further understood that reference to "an" item may refer to one or more of those items.

[0210] The steps of the methods described herein may be performed in any suitable order, or simultaneously where appropriate. In addition, individual blocks may be deleted from any method without departing from the spirit and scope of the subject matter described herein. Aspects of any of the above embodiments may be combined with aspects of any other embodiment described to form further embodiments without losing the effects sought.

[0211] The term "comprising" is used herein to mean including the identified methods, blocks, or elements, but such blocks or elements do not include an exclusive list and the method or apparatus may include additional blocks or elements.

[0212] It should be understood that the above description is given as an example only, and various modifications may be made by those skilled in the art. The above description, examples and data provide a complete description of the structure and use of the example embodiments. Although various embodiments have been described above with a certain degree of particularity or with reference to one or more separate embodiments, those skilled in the art may make many changes to the disclosed embodiments without departing from the scope of this specification.

Claims

1. A device (200) for distributing elevator calls in an elevator group of an elevator system (100), the device (200) comprising: at least one processor (202); and at least one memory (204) comprising computer program code; The at least one memory (204) and the computer program code are configured to, together with the at least one processor (202), cause the apparatus (200) to at least perform: obtaining at least one current passenger traffic indicator associated with the elevator group; determining a weight of each of at least two passenger traffic optimization objectives of the passenger traffic objective function according to the obtained at least one current passenger traffic index; optimizing the passenger transportation objective function using the determined weights; and Based on the result of optimizing the passenger traffic objective function, subsequent elevator calls are assigned to elevator cars (131, 132, 133) in the elevator group.

2. The device (200) according to claim 1, wherein: The at least two passenger traffic optimization objectives include waiting time and at least one additional passenger traffic optimization objective.

3. The device (200) according to claim 2, wherein: The weight of the at least one additional passenger transportation optimization objective includes 1-ω, where ω represents the weight of waiting time.

4. The device (200) according to claim 2 or 3, wherein: The at least one additional passenger transportation optimization objective includes at least a time to arrive at a destination.

5. The device (200) according to claim 4, wherein: The at least one current passenger traffic indicator comprises a current average waiting time AWT i and the current elevator car load factor CLF i , and obtaining the at least one current passenger traffic indicator comprises: Determine at least Item and The call allocation on the passengers of the term is minimized by the sum, where i represents the elevator call allocation instance, represents the weight of the entrance floor e, represents the weight of the non-entrance floor p, WT represents the waiting time, TTD represents the time to destination; and The average waiting time and the elevator car load factor are determined based on the determined call distribution minimizing the sum.

6. The apparatus (200) of claim 5, wherein the at least one memory (204) and the computer program code are further configured to, together with the at least one processor (202), cause the apparatus (200) to at least perform: Determine the subsequent weights used for the entrance floors and subsequent weights for non-entrance floors and determining updated weights for entrance floors and non-entrance floors to be used in said subsequent elevator call assignments using exponential smoothing; where δ represents a parameter that determines how slowly the weights change.

7. The device (200) according to claim 6, wherein: Determining the weight of each of the at least two passenger traffic optimization objectives of the passenger traffic objective function comprises: The weight of the waiting time of the passenger from the entrance floor is determined based on the current average waiting time and the current elevator car load factor using a first sigmoid function: and The weights of the waiting times of passengers from non-entrance floors are determined based on the current average waiting time using a second sigmoid function: where α, β, and γ represent parameters that specify the shape of the sigmoid function.

8. The device (200) according to claim 6, wherein: Determining the weight of each of the at least two passenger traffic optimization objectives of the passenger traffic objective function comprises: The weights of the waiting times of passengers from the entrance floors and non-entrance floors are determined based on the current average waiting time using a second sigmoid function: where α, β, and γ represent parameters that specify the shape of the sigmoid function.

9. The device (200) according to claim 2 or 3, wherein: The at least one additional passenger transportation optimization objective includes transit time.

10. The device (200) according to claim 9, wherein: Obtaining the at least one current passenger traffic indicator includes determining at least one of an average transit time or an average transit time deviation following a current elevator call assignment.

11. The device (200) according to claim 10, wherein: The at least one memory (204) and the computer program code are further configured to, together with the at least one processor (202), cause the apparatus (200) to at least perform: Short term statistics are obtained regarding serviced elevator calls to facilitate determining at least one of the average transit time or the average transit time deviation.

12. The device (200) according to claim 10 or 11, wherein: Determining the weight of each of the at least two passenger traffic optimization objectives of the passenger traffic objective function comprises: The weight of the waiting time of the subsequent elevator call assignment is obtained as a correction for the difference between the destination transit time deviation and the determined average transit time deviation or the difference between the destination transit time and the determined average transit time.

13. The device (200) according to claim 12, wherein: The at least one memory (204) and the computer program code are further configured to, with the at least one processor (202), cause the apparatus (200) to obtain the correction from a controller (310).

14. The device (200) according to claim 13, wherein: The controller (310) includes a proportional-integral-derivative (PID) controller or a proportional-integral (PI) controller.

15. The device (200) according to claim 13 or 14, wherein: The passenger traffic objective function includes: ω*WT+(1-ω)*TT, or ω*WT+(1-ω)*TTD Where WT represents the sum of waiting time, TT represents the sum of transportation time, TTD represents the sum of arrival time at the destination, and ω represents the weight of the waiting time obtained for the subsequent elevator call allocation.

16. The device (200) according to claim 2 or 3, wherein: The at least one additional passenger transportation optimization objective includes at least one of arrival time at a destination or transit time and energy consumption.

17. The device (200) according to claim 16, wherein: The at least one current passenger traffic indicator comprises at least a current average waiting time associated with a first controller configured to provide a first control signal and at least one of a current average transit time or a current average transit time deviation associated with a second controller configured to provide a second control signal, wherein determining a weight for each of at least two passenger traffic optimization objectives of the passenger traffic objective function comprises determining a weight for each of the at least two passenger traffic optimization objectives based on the first control signal and the second control signal.

18. A method (500) comprising: Obtaining (501) by a device (200) for distributing elevator calls in an elevator group of an elevator system (100) at least one current passenger traffic indicator associated with the elevator group; The device (200) determines (502) a weight of each of at least two passenger traffic optimization objectives of the passenger traffic objective function based on the obtained at least one current passenger traffic index; The passenger traffic objective function is optimized (503) by the device (200) using the determined weights; and The device (200) allocates (504) subsequent elevator calls to elevator cars (131, 132, 133) in the elevator group based on the result of optimizing the passenger traffic objective function.

19. A computer program comprising instructions for causing an apparatus for distributing elevator calls in an elevator group of an elevator system to perform at least the following operations: obtaining at least one current passenger traffic indicator associated with the elevator group; determining a weight of each of at least two passenger traffic optimization objectives of the passenger traffic objective function according to the obtained at least one current passenger traffic index; optimizing the passenger transportation objective function using the determined weights; and Subsequent elevator calls are assigned to elevator cars in the elevator group based on the results of optimizing the passenger traffic objective function.

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