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Container quay berth and quay crane distribution method based on bacterial foraging optimization method

An optimization method and bacterial foraging technology, applied in genetic models, instruments, data processing applications, etc., can solve the problems of random update population, lack of solution methods, and blind search process, so as to shorten the time of information transmission and rationally allocate resources , the effect of reducing the error rate

Inactive Publication Date: 2014-01-22
SHANGHAI MARITIME UNIVERSITY
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0006] 1. The allocation of berths and quay cranes is an NP problem, and there is still a lack of effective solution methods in these studies
[0007] 2. The update population is relatively random
[0008] 3. The search process is relatively blind

Method used

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  • Container quay berth and quay crane distribution method based on bacterial foraging optimization method
  • Container quay berth and quay crane distribution method based on bacterial foraging optimization method
  • Container quay berth and quay crane distribution method based on bacterial foraging optimization method

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Embodiment

[0038] see Figure 1 to Figure 6 As shown, this method is applied to a continuous berth quayside crane integrated scheduling model.

[0039] 1. Parameter and variable definition

[0040] 1) Collection symbol definition: V={1,...,v}, a collection of ships waiting to berth; B={0,...,b}, a collection of discrete and continuous berths on the coast, 10m is a basic unit; T={ 1,···,t}, planning period time, discrete time with 1h as a unit.

[0041] 2) Parameter symbol definition: Pb i is the best berthing position of ship i; W i is the amount of container loading and unloading required on ship i; Mq i is the maximum number of operating quay cranes allowed by ship i, Sq i is the minimum number of operating quay cranes allowed by ship i, Ra i is the arrival time of ship i, Pl i is the estimated departure time of ship i, Vl is the length of ship i (safety distance has been considered), C1 i Penalty coefficient for deviation from optimal berthing position, C2 i , Delayed departur...

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Abstract

The invention discloses a container quay berth and quay crane distribution method based on a bacterial foraging optimization method. The method comprises the following steps: initializing and defining a solution space; defining a fitness function; randomly initializing the position and the speed of bacteria and selecting out the local and global optimal positions; allowing the bacteria to move in the solution space and performing chemotaxis circulation; after the chemotaxis times reach the set times, reproducing a certain proportion of individuals with high adaptive value to replace individuals with low adaptive value; performing cloning immunization on the individuals after reproduction; after the reproduction times reach the set times, performing individual migration; circulating. The invention has the benefits that the method is different from other single methods, is a new mixed algorithm combining a bacterial foraging algorithm, a particle swarm optimization, a cloning immunization algorithm and a variable field searching method, and has the advantages of the four algorithms. Through the adoption of the method, the efficiency of a wharf can be improved, resources are distributed reasonably, the congestion phenomenon is avoided, the information transfer time is shortened and the error rate of operation is reduced.

Description

technical field [0001] The invention relates to a method for allocating berths and quayside bridges of a container terminal. Background technique [0002] The allocation of berths and quay cranes in container terminals is an important part of container operations, usually the bottleneck of operations. Therefore, the reasonable allocation of berths and quay cranes is an important means to improve the efficiency of container terminal operations. [0003] So far, many researchers at home and abroad have proposed many strategies to solve the allocation of berths and quay cranes in container terminals. In 1990, Peterkofsky et al. proposed a static quay crane scheduling strategy to minimize the cost of ship arrival and departure delays. Imai et al. explored an allocation method based on discrete berths and quay bridges in 2001, and adopted a heuristic algorithm based on Lagrangian relaxation to reduce the time for ships to receive services. In 2003, Park et al. comprehensively s...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/04G06Q10/08G06Q50/28G06N3/12
Inventor 谭盛强朱谨常奇付翔
Owner SHANGHAI MARITIME UNIVERSITY
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