Bi-objective optimization approaches to many-to-many hub location routing with distance balancing and hard time window

Taking cold-chain logistics as the research background and combining with the overall optimisation of logistics distribution networks, we develop two-stage distribution location-routing model with the minimum total cost as the objective function and varying vehicle capacity in different delivery stages. A hybrid genetic algorithm is designed based on coupling and collaboration of the two-stage routing and transfer stations. The validity and feasibility of the model and algorithm are verified by conducting a randomly generated test. The optimal solutions for different objective functions of two-stage distribution location-routing are compared and analysed. Results turn out that for different distribution objectives, different distribution schemes should be employed. Finally, we compare the two-stage distribution location-routing to single-stage vehicle routing problems. It is found that a two-stage distribution location-routing system is feasible and effective for the cold-chain logistics network, and can decrease distribution cost for cold-chain logistics enterprises.

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A simple hyper-heuristic approach for a variant of many-to-many hub location-routing problem

Journal of Heuristics ◽

10.1007/s10732-021-09477-x ◽

2021 ◽

Author(s):

Venkatesh Pandiri ◽

Alok Singh

Keyword(s):

Heuristic Approach ◽

Hub Location ◽

Location Routing Problem ◽

Routing Problem ◽

Location Routing

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A hybrid ant colony algorithm based on multiple strategies for the vehicle routing problem with time windows

Complex & Intelligent Systems ◽

10.1007/s40747-021-00401-1 ◽

2021 ◽

Author(s):

Hongguang Wu ◽

Yuelin Gao ◽

Wanting Wang ◽

Ziyu Zhang

Keyword(s):

Vehicle Routing ◽

Vehicle Routing Problem ◽

Ant Colony Algorithm ◽

Time Window ◽

Time Windows ◽

Ant Colony ◽

Routing Problem ◽

Multiple Strategies ◽

Hard Time ◽

Mutation Operation

AbstractIn this paper, we propose a vehicle routing problem with time windows (TWVRP). In this problem, we consider a hard time constraint that the fleet can only serve customers within a specific time window. To solve this problem, a hybrid ant colony (HACO) algorithm is proposed based on ant colony algorithm and mutation operation. The HACO algorithm proposed has three innovations: the first is to update pheromones with a new method; the second is the introduction of adaptive parameters; and the third is to add the mutation operation. A famous Solomon instance is used to evaluate the performance of the proposed algorithm. Experimental results show that HACO algorithm is effective against solving the problem of vehicle routing with time windows. Besides, the proposed algorithm also has practical implications for vehicle routing problem and the results show that it is applicable and effective in practical problems.

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A Synchronous Optimization Model for Multiship Shuttle Tanker Fleet Design and Scheduling Considering Hard Time Window Constraint

Journal of Advanced Transportation ◽

10.1155/2018/1904340 ◽

2018 ◽

Vol 2018 ◽

pp. 1-8

Author(s):

Zhenfeng Jiang ◽

Dongxu Chen ◽

Zhongzhen Yang

Keyword(s):

Time Window ◽

Programming Model ◽

Transportation Cost ◽

Exact Algorithm ◽

Mixed Integer ◽

Routing Problem ◽

Hard Time ◽

Proposed Model ◽

Total Transportation Cost ◽

Time Window Constraints

A Synchronous Optimization for Multiship Shuttle Tanker Fleet Design and Scheduling is solved in the context of development of floating production storage and offloading device (FPSO). In this paper, the shuttle tanker fleet scheduling problem is considered as a vehicle routing problem with hard time window constraints. A mixed integer programming model aiming at minimizing total transportation cost is proposed to model this problem. To solve this model, we propose an exact algorithm based on the column generation and perform numerical experiments. The experiment results show that the proposed model and algorithm can effectively solve the problem.

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