Rule-based ocean transportation ship scheduling method

Abstract

The invention discloses an ocean transportation ship scheduling method based on rules, and the method comprises the following steps: building an ocean transportation ship scheduling model based on an existing shipping schedule, carrying out the initial arrangement of a failed cargo set DF, and initializing an available ship set; selecting the cargos with the longest route distance in the set DP for scheme arrangement, judging whether the no-load time and the full-load time of the cargos are in the available time window of the ship or not, updating the arrangement scheme of the cargos to a ship date table of the ship, judging whether the to-be-arranged set DP is empty or not, judging whether the arrangement failure set DF is empty or not, and outputting the ship date. According to the method, aiming at a bulk industrial material ocean ship transportation scene, a multi-cargo fleet whole ship transportation scheduling optimization model is constructed, and by setting ship screening and scheduling optimization rules, on the basis of ensuring that the whole available time of a fleet is optimal, gradual iterative optimization is carried out based on the rules, and a cargo ship transportation scheme is finally generated through arrangement; the problem solving complexity is reduced, and the algorithm optimization efficiency is improved.

Description

Technical Field

[0001] The invention relates to the field of airport environment monitoring and intelligent analysis, and in particular to a rule-based ocean transport ship scheduling method. Background Art

[0002] Internationally, bulk industrial materials (crude oil, refined oil, natural gas, chemicals, etc.) are mainly transported by shipping. Generally, the cargo owner organizes his own fleet to transport from a fixed departure port to the destination port. Its characteristics are that the routes and ports are relatively fixed, the cargo flow is large, and the flow direction is relatively stable. It has a short-term operation schedule, but the requirements are not too strict. Due to the large transportation volume of bulk industrial materials, the high economic value of goods, and the high cost of ship transportation, how to optimize the allocation of ship resources and increase the available time of ships has very important practical significance and application value. Ship scheduling optimization problems are generally nonlinear programming problems, involving many restrictive factors. Relying solely on manual experience for scheduling optimization lacks scientificity and accuracy, and the workload is large. Therefore, it is necessary to study the ship resource optimization configuration model and method for specific problems in ship transportation, so as to realize automatic ship scheduling optimization and auxiliary decision-making.

[0003] 1. The Chinese patent "CN 106650980 B A method for ocean LNG supply and demand scheduling based on genetic algorithm" decomposes the ocean LNG supply and demand scheduling process into a supply single chromosome x that participates in evolutionary processes such as crossover and mutation, and a demand single chromosome y that does not participate in evolutionary processes such as crossover and mutation. By reasonably configuring the fitness value, the priorities of the three requirements of the optimization scheme, namely time matching, mismatching time difference and cargo matching, are controlled, and the optimization direction of the scheme for ocean LNG supply and demand scheduling using genetic algorithm is reasonably guided, so as to maximize the matching of ocean LNG supply and demand.

[0004] Defects: This invention mainly targets the application scenario of matching ships with specified supply quantity and supply time, demand quantity and demand time, and maximizes the number of ships that meet the supply time and delivery time range through solution scheduling, which is inconsistent with the application scenario of the present invention. In addition, this invention does not take into account the existing ship schedule, as well as the route and sailing time when two adjacent voyages are connected.

[0005] 2. The Chinese patent "CN103295061B A ship scheduling method based on ant colony algorithm" proposes an improved adaptive ant colony algorithm, adopts a new pheromone update strategy, adaptively and dynamically adjusts the pheromone p and pheromone intensity Q on the path passed by the ants that fall into local convergence, so that the algorithm can jump out of local convergence faster and prevent "premature maturity". At the same time, the pheromone values ​​on all paths are limited to a range, which is conducive to the global search of the algorithm.

[0006] Defects: This invention is aimed at scheduling routes from a designated departure port to a destination port, which is inconsistent with the application scenario of the present invention and does not take into account the time limit requirements for cargo loading. Summary of the invention

[0007] The purpose of this invention is to address the existing problems and to propose a rule-based ocean transport ship scheduling method for the scenario of ocean transport of bulk industrial materials. Based on the established ship transport scheduling model and rules, it will iteratively optimize and generate ship transport plans for bulk industrial materials to improve decision-making efficiency and scientificity.

[0008] In order to achieve the above object, the technical solution adopted by the present invention is: a rule-based ocean transport ship scheduling method, the method steps are as follows:

[0009] Step 1: Establish an ocean shipping ship scheduling model based on the existing shipping schedule;

[0010] Step 2: Given a set of goods to be arranged DP, and initializing a set of goods that failed to be arranged DF;

[0011] Step 3: Initialize the set of available ships for cargo and Said It consists of ships with non-empty transport plans in the ship set S, It consists of ships with empty transport plans in the ship set S;

[0012] Step 4: Calculate the route distances in the cargo set DP to be arranged, and select the cargo dp with the longest loading and unloading route distance in the set DP k Arrange the plan;

[0013] Step 5: Set the ship's cargo capacity to be less than the cargo dp k Loading volume of the ship, from cargo dp k Available ship set SG(dp k )

[0014] Step 6: dp the goods k Loading time window tg(dp k ) Ships with cargo transportation plans, from cargo dp k Available ship set SG(dp k )

[0015] Step 7: Determine the available ship set SG(dp k ) is empty, if SG(dp k ) is empty, indicating that the goods dp k No available ship, jump to step 11; if SG(dp k ) is not empty, jump to the next step;

[0016] Step 8: According to the goods dp k Loading time window tg(dp k ), loading and unloading routes, existing transportation plans for ships, and all ships i ∈SG(dp k ), determine the cargo dp k Whether the empty time and full load time of the ship are within the available time window of the ship, for cargo dp k The ships in the transport time window are calculated to arrange the plan sch(s i , dp k ) and the reduction in optimization time Δopt(s i , dp k ), for no goods dp k The ship of the transportation time window is selected from the available ship set SG(dp k )

[0017] Step 9: Determine the available ship set SG(dp k ) is empty, if the available ship set SG(dp k ) is empty, indicating that the goods dp k Arrangement fails, jump to step 11; if the available ship set SG (dp k ) is not empty, jump to the next step;

[0018] Step 10, solve min Δopt(s i , dp k ), s i ∈SG(dp k ) Corresponding ships k , as cargo dp k The optimal arrangement scheme sch o (s k , dpk), the goods dp k The arrangement scheme of sch o (s k , dp k ) Update to ships k Sailing Schedule dp the goods k Add to the arranged goods collection D, and at the same time transfer the goods dp k Delete from the set to be arranged DP, that is: DP = DP-dp k , and jump to step 12;

[0019] Step 11: dp the goods k Add it to the failed arrangement set DF, delete it from the to-be-arranged set DP, and jump to the next step;

[0020] Step 12: determine whether the set to be arranged DP is empty. If the set to be arranged DP is not empty, jump to step 4 to arrange the next cargo. If the failed arrangement set DP is empty, it means there is no cargo to be arranged, jump to the next step.

[0021] Step 13: Determine whether the failed arrangement set DF is empty. If the failed arrangement set DF is empty, it means that all cargoes are arranged successfully, and the updated ship schedule is output; if the failed arrangement set DF is not empty, it is necessary to determine the set of ships with empty schedules. Is it empty? If the collection If it is empty, it means that the goods in the set DF cannot be arranged in all available ships, which means that the arrangement of the goods in the set DF has failed, and the ship schedule of the successfully arranged goods is output.

[0022] Preferably, in step 1, the objective function of the ocean transport ship scheduling model based on the existing ship schedule is:

[0023]

[0024] in: It is a collection of non-empty ships on the sailing schedule; is the number of non-empty ships on the sailing schedule; It is the available time of a non-empty vessel.

[0025] Preferably, the constraints of the ocean transport ship scheduling model based on the existing ship schedule are as follows:

[0026] Ship collection: S, s i ∈S, i = 1, ..., n, i represents the number of a ship, s i represents the ship numbered i, and n represents the total number of n ships in the set S;

[0027] The collection of ships with non-empty sailing schedules: in Representing a collection There are A non-empty vessel on a sailing schedule;

[0028] Ship standard speed set: V, v(s i )∈V,s i ∈S;

[0029] Ship cargo capacity collection: SC, sc(s i )∈SC,s i ∈Ssc(s i ) indicates ships i of cargo capacity;

[0030] Vessel lease term: T, Respectively represent the start and end time of the lease of vessel i;

[0031] Goods set: D, d1∈D, l=1,...,m, l represents a certain goods number, d l represents the goods numbered l, and m represents the total number of goods in set D;

[0032] Cargo loading SZ, sz(d l )∈SZ,d l ∈Dsz(d l ) indicates goods d l Loading capacity;

[0033] Cargo loading time collection: tg(d l )∈TG, d l ∈Dtg(d l ) represents the loading start time and loading end time of cargo d1;

[0034] Cargo loading port collection: PO, po(d l )∈PO,d1∈DCpo(d l ) indicates the port of loading of cargo d1;

[0035] Cargo unloading port set: PD, pd(d1)∈PD,d l ∈DCpd(d1) represents the quantity of goods d l Unloading port;

[0036] The port route distance is expressed as:

[0037] rt(po(d l ),pd(d l ))∈RT,po(d l )∈PO,pd(d l )∈PD

[0038] Among them, rt(po(d l ), pd(d l )) indicates port po(d l ) to port pd(d l ) between the two routes;

[0039] Ships i From the port po(d l ) to port pd(d l )’s flight time is expressed as:

[0040] Δt(po(d l ), pd(d l ), v(si ))=rt(po(d l ),pd(d l )) / v(s i );

[0041] Ships i A collection of transport plans:

[0042]

[0043] Among them, ST(s i ) indicates ships i The transport time window set, SD(s i ) indicates ships i The transport cargo collection;

[0044]

[0045] Where j1=1, ..., p(s i ), where j1 represents the ship s i The j1th transportation plan of

[0046] Among them, p(s i ) indicates ships i ∈S has p(s i ) transport plans.

[0047] Preferably, the ocean transport ship scheduling model based on the existing ship schedule plan is:

[0048] Ships i The time corresponding to the j1th transportation plan is expressed as:

[0049]

[0050] in, Indicates ships i The start time of the j1th transportation plan,

[0051] in, Indicates ships i The end time of the j1th transportation plan;

[0052] Ships i The goods corresponding to the j1th transportation plan are expressed as:

[0053] The minimum available time of a ship is: Tmin;

[0054] According to the ships i The transportation plan can be derived from the ship s i The available time window set OPT(si ):

[0055]

[0056] Where j2 represents the ship s i The j2th available time window;

[0057] represents the start time of the j2th available time window; The end time of the j2th available time window;

[0058] Ships i Available time:

[0059]

[0060] Among them, the function

[0061] Solving the above ship scheduling optimization model, we can get cargo d i The corresponding feasible solution set SCH(s i , d l )for:

[0062]

[0063] Among them, t(s i )and Ships i For this cargo l The start and end time of the transportation plan;

[0064] Cargo l The corresponding optimal arrangement solution is defined as:

[0065]

[0066] Among them, t o (s i )and Ships i For this cargo l The start and end time points of the optimal transportation plan.

[0067] As a preferred embodiment, in step 2, a set of goods to be arranged DP is given, wherein and ships i ∈S, i = 1, ..., n, where Indicates the number b of the goods to be arranged.

[0068] As a preferred method, in step 3, Collection of ships and The initialization process is as follows:

[0069] For all s i ∈S,

[0070] For all s i ∈S,

[0071] Among them, ST(s i ) indicates ships i The set of transport time windows.

[0072] As a preferred method, in step 4, the cargo dp with the longest loading and unloading route distance in the set DP is k The formula for arranging the plan is as follows:

[0073]

[0074] As a preferred method, in step eight, determine the cargo dp k Whether the empty time and full load time of the ship are within the available time window of the ship, and calculate the arrangement scheme sch(s i , dp k ) and the optimized time base small amount Δopt(s i , dp k ) is as follows,

[0075] 1) For all ships i ∈SG(dp k ), IF t (dp k )≥ T (s i ),

[0076] and This means that the ship i Able to arrange cargo dp k ;

[0077] Its arrangement scheme sch(s i , dp k )for:

[0078]

[0079] Use this window to arrange goods dp k , ships i The reduction in optimization time Δopt(s i , dp k )for:

[0080]

[0081] 2) For all ships i ∈SG(dp k )

[0082] and

[0083] This means that the ship i Able to arrange cargo dp k ;

[0084] Arrangement scheme sch(s i , dp k )for:

[0085]

[0086] Use this window to arrange goods dp k , ships i The reduction in optimization time Δopt(s i , dp k )for

[0087]

[0088] 3) For all ships i ∈SG(dp k ) and j1=1,...,p(s i ),

[0089] and

[0090]

[0091] This means that the ship i Able to arrange cargo dp k ;

[0092] Arrangement scheme sch(s i , dp k )for

[0093]

[0094] Use this window to arrange goods dp k , ships i The total reduction in optimizable time Δopt(s i , dp k )for

[0095]

[0096] 4) If one of the above conditions is met, it means that the cargo can be arranged in the ship. If none of the above three conditions are met, it means that the ship is i There is no product dp k If the transport time window fails, the ship s i From cargo dp k Available ship set SG(dp k ) in the elimination, that is, SG(dp k )=SG(dp k )-s i .

[0097] As a preferred embodiment, in step thirteen, if the set If it is not empty, then the set of ships whose sailing schedule is empty is required. To arrange the goods, the steps are as follows:

[0098] Step 14: Select a collection The ship with the smallest cargo capacity is added to the set as the available ship for the failed cargo set DF. and remove the ship with the smallest calculated cargo capacity from the set Delete from;

[0099] Step 15: add the goods in the failed arrangement goods set DF to the to-be-arranged goods set DP, delete all the goods in the DF set, and jump to step 4 for rearrangement.

[0100] Compared with the prior art, the advantages of the present invention are as follows: the present invention aims at the ocean-going ship transportation scenario of bulk industrial materials, constructs a multi-cargo fleet ship transportation scheduling optimization model, and by setting ship screening and scheduling optimization rules, on the basis of ensuring the optimal overall available time of the fleet, gradually iteratively optimizes and finally arranges the generated cargo ship transportation plan based on the rules, thereby reducing the complexity of problem solving and improving the efficiency of algorithm optimization. BRIEF DESCRIPTION OF THE DRAWINGS

[0101] Figure 1 The present invention is a flow chart of the method for rule-based ocean transport vessel scheduling.

[0102] Figure 2 This is a schematic diagram of the cargo and ship transportation plan to be arranged.

[0103] Figure 3 A result diagram is provided for arranging the ocean transport vessel scheduling method based on the rules of the present invention. DETAILED DESCRIPTION

[0104] The present invention aims at the arrangement of ocean-going shipping plans for bulk industrial materials. Based on the existing ship schedule, the present invention dynamically analyzes the ship utilization time and schedules and generates a cargo transportation plan. The evaluation criteria for the quality of the scheduling results are as follows: (1) The available time of the fleet after scheduling is the longest, where the available time refers to the continuous idle time period of a ship that is not less than the required time Tmin. If the ship has available time, it means that the ship can be rented out to earn rent or can be used to optimize the arrangement of subsequent cargo during the available time. If the idle time period is too small, it means that there is a high probability that cargo will not be arranged in the idle time period. (2) The scheduling plan is arranged to ships with existing schedules as much as possible to maximize the utilization rate of existing ships.

[0105] The present invention will be further described below in conjunction with implementation cases:

[0106] 1. Establish an ocean-going vessel scheduling model based on existing ship schedules:

[0107] 1. The designed ocean shipping ship scheduling model based on the existing shipping schedule is as follows:

[0108] Objective function:

[0109] in: It is a collection of non-empty ships on the sailing schedule; is the number of non-empty ships on the sailing schedule; It is the available time of a non-empty vessel.

[0110] Interpretation: The number of ships with scheduled tasks is the least, and the available time for scheduled tasks is the largest.

[0111] Constraints:

[0112] Ship collection: S, s i ∈S, i = 1, ..., n, i represents the number of a ship, s i represents the ship numbered i, and n represents the total number of n ships in the set S;

[0113] The collection of ships with non-empty sailing schedules: in Representing a collection There are A non-empty vessel on a sailing schedule;

[0114] Ship standard speed set: V, v(s i )∈V,s i ∈S

[0115] Ship cargo capacity collection: SC, sc(s i )∈SC,s i ∈Ssc(s i) indicates ships i of cargo capacity;

[0116] Vessel lease term: T, Respectively represent the start and end time of the lease of vessel i;

[0117] Goods set: D, d1∈D, 1=1, ..., m, l represents a certain goods number, d l represents the goods numbered l, and m represents the total number of goods in set D;

[0118] Cargo loading SZ, sz(d l )∈Sz, dl∈Dsz(d1) represents the loading quantity of cargo d1;

[0119] Cargo loading time collection: tg(d l )∈TG, d l ∈Dtg(d1) represents the quantity of goods d l The loading start time and loading end time;

[0120] Cargo loading port collection: PO, po(d l )∈PO,d l ∈DCpo(d l ) indicates goods d l Loading port;

[0121] Cargo unloading port collection: PD, pd (d l )∈PD,d l ∈DCpd(d l ) indicates goods d l Unloading port;

[0122] The port route distance is expressed as:

[0123] rt(po(d l ),pd(d l ))∈RT,po(d1)∈PO,pd(d l )∈PD

[0124] Among them, rt(po(d l ), pd(d l )) indicates port po(d l ) to port pd(d l ) between the two routes;

[0125] Ships i From the port po(d l ) to port pd(d l )’s flight time is expressed as:

[0126] Δt(po(d l ), pd(d l ), v(s i ))=rt(po(d l ), pd(d1)) / v(s i )

[0127] Ships i A collection of transport plans:

[0128] PL(s i )=(ST(s i ), SD(s i ))

[0129] Among them, ST(s i ) indicates ships i The transport time window set, SD(s i ) indicates ships i of transport cargoes.

[0130]

[0131] Where j1=1, ..., p(s i ), where j1 represents the ship s i The j1th transportation plan of i ) indicates ships i ∈s has p(s i ) transport plans.

[0132] Then, the ship i The time corresponding to the j1th transportation plan is expressed as

[0133]

[0134] in Indicates ships i The start time of the j1th transportation plan, Indicates ships i The end time of the j1th transportation plan.

[0135] Ships i The goods corresponding to the j1th transportation plan are expressed as

[0136] The minimum available time of a ship is: Tmin;

[0137] According to the ships i The transportation plan can be derived from the ship s i The available time window set OPT(s i ):

[0138]

[0139] Where j2 represents the ship s i The j2th available time window;

[0140] represents the start time of the j2th available time window; The end time of the j2th available time window;

[0141] Ships i Available time:

[0142]

[0143] Among them, the function

[0144] Solving the above ship scheduling optimization model, we can get cargo d i The corresponding feasible solution set SCH(s i ,d l )for:

[0145]

[0146] in, t (s i )and Ships i For this cargo l The start and end time of the transportation plan.

[0147] Cargo l The corresponding optimal arrangement solution is defined as:

[0148]

[0149] in, t o (s i )and Ships i For this cargo l The start and end time points of the optimal transportation plan.

[0150] 2. Given a set of goods to be arranged DP, where and ships i ∈S, i = 1, ..., n, where Indicates the number of goods to be arranged.

[0151] As can be seen from the above, the present invention is based on the ocean-going shipping ship scheduling model of the existing shipping schedule: for the ocean-going shipping scenario of bulk industrial materials, a multi-cargo fleet whole ship transportation scheduling optimization model is constructed. On the basis of the existing shipping schedule of the own fleet, the ship's empty sailing time from the previous voyage to the current voyage, the full-load sailing time of the current voyage, and the impact of the cargo of the current voyage on the empty sailing time of the next voyage are dynamically analyzed to arrange the ship transportation plan, thereby making the scheduling optimization more accurate. In addition, by constructing an available time index, the available time of the ship is maximized, providing support for arranging the next cargo or leasing within the available time of the ship, and improving the overall utilization rate of the fleet.

[0152] 2. Using a rule-based ocean-going ship scheduling method designed by the present invention to solve the optimal arrangement scheme The steps are as follows, see Figure 1 :

[0153] (1) Initialize the failed arrangement goods set DF to an empty set, that is:

[0154] (2) Initialize goods A collection of available ships and

[0155] in, It consists of ships with non-empty transport plans in the ship set S, It consists of the ships whose transportation plans are empty in the ship set S.

[0156] For goods Collection of ships and The initialization process is as follows:

[0157] For all s i ∈S,

[0158] For all s i ∈S,

[0159] Among them, ST(s i ) indicates ships i The set of transport time windows;

[0160] (3) Calculate the route distances in the set of goods to be arranged DP, and first arrange the goods dp with the longest route distance in the set DP. k :

[0161]

[0162] (4) According to the ship's cargo capacity and cargo loading, the ship's cargo capacity is less than the cargo dp k Loading volume of the ship from cargo dp k Available ship set SG(dp k ), that is, for all s i ∈SG(dp k ),

[0163] IFsc(s i )<sz(dp k ):SG(dp k )=SG(dp k )-s i ;

[0164] (5) dp the goods k Loading time window tg(dp k ) Ships with cargo transportation plans from cargo dp k Available ship set SG(dp k ), that is, for all s i ∈SG(dp k ),

[0165] or

[0166] (6) Determine SG(dp k ) is empty. If SG(dp k ) is empty, indicating that the goods dp k No available ship, jump to step 10; if SG(dp k ) is not empty, jump to the next step 7.

[0167] (7) For all ships i ∈SG(dp k ), calculate the cargo dp k Available arrangement schemes are calculated as follows:

[0168] 1) For all ships i ∈SG(dp k ),

[0169] IF t (dp k )≥ T (s i ),

[0170] and

[0171] This means that the ship i Able to arrange cargo dp k;

[0172] Its arrangement scheme sch(s i , dp k )for:

[0173]

[0174] Use this window to arrange goods dp k , ships i The time-optimized base is small amount Δopt(s i , dp k )for:

[0175]

[0176] 2) For all ships i ∈SG(dp k )

[0177] and

[0178]

[0179] This means that the ship i Able to arrange cargo dp k ;

[0180] Arrangement scheme sch(s i , dp k )for

[0181]

[0182] Use this window to arrange goods dp k , ships i The reduction in optimization time Δopt(s i , dp k )for

[0183]

[0184] 3) For all ships i ∈SG(dp k ) and j1=1,...,p(s i ),

[0185] and

[0186]

[0187] This means that the ship i Able to arrange cargo dp k , arrangement scheme sch(s i , dpk )for

[0188]

[0189] Use this window to arrange goods dp k , ships i The total alkali amount that can be optimized for a short time Δopt(s i , dp k )for

[0190]

[0191] 4) If one of the above conditions is met, it means that the cargo can be arranged in the ship. If none of the above three conditions are met, it means that the ship is i There is no product dp k The transport time window is too short, and the arrangement fails. Then ship s i From cargo dp k Available ship set SG(dp k ) in the elimination, that is, SG(dp k )=SG(dp k )-s i .

[0192] (8) Determine SG(dp k ) is empty. If SG(dp k ) is empty, indicating that the goods dp k Arrangement fails, jump to step 10; if SG(dp k ) is not empty, jump to the next step 9.

[0193] (9) Solve minΔopt(s i , dp k ), s i ∈SG(dp k ) Corresponding ships k , as cargo dp k The optimal arrangement scheme sch o (s k , dp k ). dp the goods k The arrangement scheme of sch o (s k , dp k ) Update to ships k Sailing Schedule dp the goods k Add to the arranged goods collection D, and at the same time transfer the goods dp k Delete from the set to be arranged DP, that is: DP = DP-dp k , and skip to step 11.

[0194] (10) dp k Add to the arrangement failure set DF, that is: DF = DF∪dp k ; Set dp k Delete from the set to be arranged DP, that is: DP = DP-dp k , skip to the next step 11.

[0195] (11) Determine whether the set to be arranged DP is empty. If the set DP is not empty, jump to step 3 to arrange the next cargo. If the set DP is empty, it means that there is no cargo to be arranged, jump to the next step 12.

[0196] (12) If the set DF is empty, return "all cargoes are arranged successfully" and output the updated ship schedule. If DF is not empty, it is necessary to determine the set of ships with empty schedules. Is it empty? If the collection If it is empty, it means that the goods in the set DF cannot be arranged in all available ships, and the "failed to arrange the goods in the set DF" is returned, and the ship schedule of the successfully arranged goods is output; if the set If it is not empty, then the set of ships with empty sailing schedules is required. Arrange the goods in the middle and skip to the next step 13.

[0197] (13) Select a set The smallest cargo ship, As an available ship for the failed cargo collection DF, add it to the collection and remove the ship with the smallest calculated cargo capacity from the set Delete it.

[0198] (14) Add the goods in the failed arrangement goods set DF back to the to-be-arranged goods set DP, and delete all the goods in the DF set, that is: Skip to step 3 to rearrange.

[0199] In summary, the present invention is a rule-based ocean-going ship scheduling method: for the constructed nonlinear optimization problem of ship scheduling, the complexity of problem solving and the best solution are comprehensively considered, and a rule-based ocean-going ship scheduling method is proposed. Based on a large amount of prior data analysis, arrangement rules such as giving priority to arranging cargoes with long sailing times and giving priority to the use of arranged cargo ships are set, and the screening of ships and scheme optimization are performed based on various rules. On the basis of ensuring the available time of the arrangement scheme, the number of iterative optimizations can be significantly reduced, and the success rate of the scheme arrangement and the utilization rate of ships can be improved. And for the optimization problem of M cargoes and N ships, the maximum number of algorithm iterative optimizations is M×N. On the basis of ensuring the available time, the number of iterative optimizations is increased to improve the success rate of the arrangement and the utilization rate of ships.

[0200] The examples are as follows:

[0201] S1: Assume that there are 3 ships in the fleet, numbered as ship 1, ship 2, and ship 3. Figure 2 As shown, a transportation plan for cargo 6 needs to be formulated, wherein the loading information of cargo 6 is shown in the following table.

[0202] Table 1 Goods 6 Details

[0203] type Details Loading start time July 12 Loading end time July 13 Loading port Port of Savannah(USA) Unloading Port Fangchenggang(China) Route distance 14,000 nautical miles Average speed 16th section Sailing time 36 days Loading capacity 80,000 tons

[0204] S2: After adopting the ocean transport ship dispatching method of the present invention, Figure 3 It can be seen that ship 1, ship 2, and ship 3 all have transportation time windows that meet the cargo of the ship. It can be seen that by using the rule-based ocean transport ship scheduling method of the present invention, based on the optimization objectives of minimizing the number of non-empty ships on the ship schedule and maximizing the available time of non-empty ships on the ship schedule, the optimal transportation plan for cargo 6 can be solved as ship 1, and its transportation plan is [June 15, July 29], where [June 15, July 12] is the sailing time from the unloading port of cargo 6 on the previous voyage to the loading port of this voyage, and [July 13, July 29] is the sailing time from the loading port of this voyage to the unloading port.

[0205] The above is a detailed introduction to a rule-based ocean transport ship scheduling method provided by the present invention. Specific examples are used in this article to illustrate the principles and implementation methods of the present invention. The description of the above embodiments is only used to help understand the method of the present invention and its core idea; at the same time, for those skilled in the art, according to the idea of ​​the present invention, there will be changes in the specific implementation method and application scope, and changes and improvements to the present invention will be possible without exceeding the concept and scope specified in the attached claims. In summary, the content of this specification should not be understood as limiting the present invention.

Claims

1. A rule-based ocean transport ship scheduling method, characterized in that: The method steps are as follows: Step 1: Establish an ocean shipping ship scheduling model based on the existing shipping schedule; Step 2: Given a set of goods to be arranged DP, and initializing a set of goods that failed to be arranged DF; Step 3: Initialize the set of available ships for cargo and Said It consists of ships with non-empty transport plans in the ship set S, It consists of ships with empty transport plans in the ship set S; Step 4: Calculate the route distances in the cargo set DP to be arranged, and select the cargo dp with the longest loading and unloading route distance in the set DP k Arrange the plan; Step 5: Set the ship's cargo capacity to be less than the cargo dp k Loading volume of the ship, from cargo dp k Available ship set SG(dp k ) Step 6: dp the goods k Loading time window tg(dp k ) Ships with cargo transportation plans, from cargo dp k Available ship set SG(dp k ) Step 7: Determine the available ship set SG(dp k ) is empty, if SG(dp k ) is empty, indicating that the goods dp k No available ship, jump to step 11; if SG(dp k ) is not empty, jump to the next step; Step 8: According to the goods dp k Loading time window tg(dp k ), loading and unloading routes, existing transportation plans for ships, and all ships i ∈SG(dp k ), determine the cargo dp k Whether the empty time and full load time of the ship are within the available time window of the ship, for cargo dp k The ships in the transport time window are calculated to arrange the plan sch(s i , dp k ) and the reduction in optimization time Δopt(s i , dp k ), for no goods dp k The ship of the transportation time window is selected from the available ship set SG(dp k ) Step 9: Determine the available ship set SG(dp k ) is empty, if the available ship set SG(dp k ) is empty, indicating that the goods dp k Arrangement fails, jump to step 11; if the available ship set SG (dp k ) is not empty, jump to the next step; Step 10, solve min Δopt(s i , dp k ), s i ∈SG(dp k ) Corresponding ships k , as cargo dp k The optimal arrangement scheme sch o (s k , dp k ), dp the goods k The arrangement scheme scho(s k , dp k ) Update to ships k The shipping schedule (st j1 (s k ), dp k ), dp the goods k Add to the arranged goods collection D, and at the same time transfer the goods dp k Delete from the set to be arranged DP, that is: DP = DP-dp k , and jump to step 12; Step 11: dp the goods k Add it to the failed arrangement set DF, delete it from the to-be-arranged set DP, and jump to the next step; Step 12: determine whether the set to be arranged DP is empty. If the set to be arranged DP is not empty, jump to step 4 to arrange the next cargo. If the failed arrangement set DP is empty, it means there is no cargo to be arranged, and jump to the next step; Step 13: determine whether the failed arrangement set DF is empty. If the failed arrangement set DF is empty, it means that all cargoes are arranged successfully, and the updated ship schedule is output; If the arrangement failure set DF is not empty, it is necessary to determine the set of ships whose sailing schedules are empty. Is it empty? If the collection If it is empty, it means that the goods in the set DF cannot be arranged in all available ships, which means that the arrangement of the goods in the set DF has failed, and the ship schedule of the successfully arranged goods is output.

2. A rule-based ocean transport ship scheduling method according to claim 1, characterized in that: In step 1, the objective function of the ocean transport ship scheduling model based on the existing ship schedule is in: It is a collection of non-empty ships on the sailing schedule; is the number of non-empty ships on the sailing schedule; It is the available time of a non-empty vessel.

3. A rule-based ocean transport ship scheduling method according to claim 2, characterized in that: The constraints of the ocean shipping ship scheduling model based on the existing ship schedule are as follows: Ship collection: S, s i ∈S, i = 1, ..., n, i represents the number of a ship, s i represents the ship numbered i, and n represents the total number of n ships in the set S; The collection of ships with non-empty sailing schedules: in Representing a collection There are A non-empty vessel on the sailing schedule; Ship standard speed set: V, v(s i )∈C,s i ∈S; Ship cargo capacity collection: SC, sc(s i )∈SC,s i ∈Ssc(s i ) indicates ships i of cargo capacity; Vessel lease term: T, Respectively represent the start and end time of the lease of vessel i; Goods collection: D, d l ∈D, 1=1,...,m,l represents a certain product number, d l represents the goods numbered 1, and m represents the total number of goods in set D; Cargo loading SZ, sz(d l )∈SZ,d l ∈Dsz(d l ) indicates goods d l The loading capacity; The cargo loading time set: tg(dx)∈TG, d l ∈Dtg(d l ) indicates goods d l The loading start time and loading end time; Cargo loading port collection: PO, po(d l )∈PO,d l ∈DCpo(d l ) indicates goods d l Loading port; Cargo unloading port collection: PD, pd (d l )∈PD,d l ∈DCpd(d l ) indicates goods d l Unloading port; The port route distance is expressed as: rt(po(d l ),pd(d l ))∈RT,po(d l )∈PO,pd(d l )∈PD Among them, rt(po(d l ), pd(d l )) represents the route distance between port po(dl) and port pd(dl); Ships i From the port po(d l ) to port pd(d l )’s flight time is expressed as: Δt(po(d l ),pd(d l ),v(s i ))=rt(po(d l ),pd(d l )) / v(s i ); Ships i A collection of transport plans: PL(s i )=(ST(s i ),SD(s i )) Among them, ST(s i ) indicates ships i The transport time window set, SD(s i ) indicates ships i The transport cargo collection; Where j1=1, ..., p(s i ), where j1 represents the ship s i The j1th transportation plan of Among them, p(s i ) indicates ships i ∈S has p(s i ) transport plans.

4. A rule-based ocean transport ship scheduling method according to claim 3, characterized in that: The ocean-going vessel scheduling model based on the existing ship schedule is Ships i The time corresponding to the j1th transportation plan is expressed as: in, Indicates ships i The start time of the j1th transportation plan, in, Indicates ships i The end time of the j1th transportation plan; Ships i The goods corresponding to the j1th transportation plan are expressed as: The minimum available time of a ship is: Tmin; According to the ships i The transportation plan can be derived from the ship s i The available time window set OPT(s i ): Where j2 represents the ship s i The j2th available time window; represents the start time of the j2th available time window; The end time of the j2th available time window; Ships i Available time: in, Solving the above ship scheduling optimization model, we can get cargo d i The corresponding feasible solution set SCH(s i , d l )for: Among them, t(s i )and Ships i For this cargo l The start and end time of the transportation plan; Cargo l The corresponding optimal arrangement solution is defined as: in, and Ships i For this cargo l The start and end time points of the optimal transportation plan.

5. The rule-based ocean-going vessel scheduling method according to claim 1, characterized in that: In step 2, a set of goods to be arranged DP is given, where and ships i ∈S, i = 1, ..., n, where Indicates the number b of the goods to be arranged.

6. The rule-based ocean-going vessel scheduling method according to claim 1, characterized in that: In step three, Collection of ships and The initialization process is as follows: For all s i ∈S, For all s i ∈S, Among them, ST(s i ) indicates ships i The set of transport time windows.

7. The rule-based ocean-going vessel scheduling method according to claim 1, characterized in that: In step 4, the cargo dp with the longest loading and unloading route distance in the set DP is k The formula for arranging the plan is as follows:

8. The rule-based ocean-going vessel scheduling method according to claim 1, characterized in that: In step 8, determine the cargo dp k Whether the empty time and full load time of the ship are within the available time window of the ship, and calculate the arrangement scheme sch(s i , dp k ) and the optimized time base small amount Δopt(s i , dp k ) is as follows, 1) For all ships i ∈SG(dp k ), IF t (dp k )≥ T (s i ), and This means that the ship i Able to arrange cargo dp k ; Its arrangement scheme sch(s i , dp k )for: Use this window to arrange goods dp k , ships i The reduction in optimization time Δopt(s i , dp k )for: 2) For all ships i ∈SG(dp k ) and This means that the ship i Able to arrange cargo dp k ; Arrangement scheme sch(s i , dp k )for Use this window to arrange goods dp k , ships i The time-optimized base is a small amount of Δopt(s i , dp k )for 3) For all ships i ∈SG(dp k ) and j1=1,...,p(s i ), and This means that the ship i Able to arrange cargo dp k ; Arrangement scheme sch(s i , dp k )for: Use this window to arrange goods dp k , ships i The total reduction in optimizable time Δopt(s i , dp k )for 4) If one of the above conditions is met, it means that the cargo can be arranged in the ship. If none of the above three conditions are met, it means that the ship is i There is no product dp k If the transport time window fails, the ship s i From cargo dp k Available ship set SG(dp k ) in the elimination, that is, SG(dp k )=SG(dp k )-s i .

9. The rule-based ocean-going vessel scheduling method according to claim 1, characterized in that: In step 13, if the set If it is not empty, then the set of ships with empty sailing schedules is required. To arrange the goods, the steps are as follows: Step 14: Select a collection The ship with the smallest cargo capacity is added to the set as the available ship for the failed cargo set DF. and remove the ship with the smallest calculated cargo capacity from the set Delete from; Step 15: add the goods in the failed arrangement goods set DF to the to-be-arranged goods set DP, delete all the goods in the DF set, and jump to step 4 for rearrangement.

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