A new optimization algorithm for the vehicle routing problem with time windows
Operations Research
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Computers in Industry
Exact solution of large-scale, asymmetric traveling salesman problems
ACM Transactions on Mathematical Software (TOMS)
Modeling rolling batch planning as vehicle routing problem with time windows
Computers and Operations Research
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MACS-VRPTW: a multiple ant colony system for vehicle routing problems with time windows
New ideas in optimization
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Transportation Science
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Computers and Industrial Engineering - Special issue: Selected papers from the 25th international conference on computers & industrial engineering in New Orleans, Louisiana
Traveling Salesman Problems with Profits
Transportation Science
A hybrid Lagrangian genetic algorithm for the prize collecting Steiner tree problem
Computers and Operations Research
Lagrangian duality applied to the vehicle routing problem with time windows
Computers and Operations Research
Binary integer programming formulations for scheduling in market-driven foundries
Computers and Industrial Engineering
Collaborative optimization under a control framework for ATSP
ICSI'11 Proceedings of the Second international conference on Advances in swarm intelligence - Volume Part I
A model induced max-min ant colony optimization for asymmetric traveling salesman problem
Applied Soft Computing
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This paper presents a transparent model and a solution approach to solve a large-scale rolling batch scheduling problem. First, the problem is formulated as a multiple routes problem with multi-objective (MRMOP). By defining a hierarchical cost structure it is natural to decompose the MRMOP into several well-studied sub-problems, i.e. the multiple routes minimum cost problem (MRMCP), the knapsack problem (KP) and the linear assignment problem (LAP). Among these sub-problems the MRMCP is considered as the central one and is tackled first of all. The solution procedure for the MRMCP is based on a partial set-partitioning formulation. It makes use of a variant of column generation. Feasible column is generated as needed by solving a resource constrained elementary shortest path problem (RC-ESPP) by a mixed strategy combing an exact method and heuristics. Then a procedure called Adding-Node is introduced to implicitly solve the KP starting from the solution of the MRMCP. Finally, we solve the LAP with Hungarian algorithm to consider the total tardiness and earliness of the production. Computational results are presented compared with several promising methods on benchmark problems and production orders from Shanghai Baoshan Iron and Steel Complex. The results demonstrate the efficiency of the proposed algorithm.