A cross decomposition algorithm for a multiproduct-multitype facility location problem
Computers and Operations Research
Genetic algorithms + data structures = evolution programs (2nd, extended ed.)
Genetic algorithms + data structures = evolution programs (2nd, extended ed.)
An approach to a problem in network design using genetic algorithms
An approach to a problem in network design using genetic algorithms
Computers and Operations Research
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms
A multiobjective hybrid genetic algorithm for the capacitatedmultipoint network design problem
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
A genetic algorithm approach for multi-objective optimization of supply chain networks
Computers and Industrial Engineering - Special issue: Computational intelligence and information technology applications to industrial engineering selected papers from the 33 rd ICC&IE
Information Sciences: an International Journal
Decomposition heuristic to minimize total cost in a multi-level supply chain network
Computers and Industrial Engineering
4/R/I/T distribution logistics network 0-1 programming model and application
Computers and Industrial Engineering
A SOLUTION OF REAL-WORLD OCST PROBLEMS WITH A NEW TREE ENCODING-BASED GENETIC ALGORITHM
Cybernetics and Systems
A steady-state genetic algorithm for multi-product supply chain network design
Computers and Industrial Engineering
Computers and Industrial Engineering
A class of random fuzzy programming and its application to supply chain design
Computers and Industrial Engineering
A genetic algorithm approach for multi-objective optimization of supply chain networks
Computers and Industrial Engineering
Computers and Industrial Engineering
A closed-loop logistic model with a spanning-tree based genetic algorithm
Computers and Operations Research
A memetic algorithm for bi-objective integrated forward/reverse logistics network design
Computers and Operations Research
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Review article: A review of soft computing applications in supply chain management
Applied Soft Computing
Expert Systems with Applications: An International Journal
Computers and Industrial Engineering
Computers and Industrial Engineering
Expert Systems with Applications: An International Journal
Network optimization in supply chain: A KBGA approach
Decision Support Systems
A genetic algorithm for solving the fixed-charge transportation model: Two-stage problem
Computers and Operations Research
A possibilistic approach to the modeling and resolution of uncertain closed-loop logistics
Fuzzy Optimization and Decision Making
Analysis of different approaches to cross-dock truck scheduling with truck arrival time uncertainty
Computers and Industrial Engineering
Expert Systems with Applications: An International Journal
Multi objective outbound logistics network design for a manufacturing supply chain
Journal of Intelligent Manufacturing
Information Sciences: an International Journal
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In recent years, many of the developments in logistics are connected to the need of information of efficient supply chain flow. An important issue in the logistics system is to find the network strategy that can give the least cost of the physical distribution flow. In this paper, we consider the logistic chain network problem formulated by 0-1 mixed integer linear programming model. The design tasks of this problem involve the choice of the facilities (plants and distribution centers) to be opened and the distribution network design to satisfy the demand with minimum cost. As the solution method, we propose the spanning tree-based genetic algorithm by using Prüfer number representation. We design the feasibility criteria and develop the repairing procedure for the infeasible Prüfer number, so that it can work for relatively large size problems. The efficacy and the efficiency of this method are demonstrated by comparing its numerical experiment results with those of traditional matrix-based genetic algorithm and professional software package LINDO.