Multi-objective genetic algorithm and its applications to flowshop scheduling
Computers and Industrial Engineering
Evolutionary Algorithms for Solving Multi-Objective Problems
Evolutionary Algorithms for Solving Multi-Objective Problems
A model and methodologies for the location problem with logistical components
Computers and Operations Research
Study on multi-stage logistic chain network: a spanning tree-based genetic algorithm approach
Computers and Industrial Engineering - Supply chain management
A strategic model for supply chain design with logical constraints: formulation and solution
Computers and Operations Research
Hybrid genetic algorithm for multi-time period production/distribution planning
Computers and Industrial Engineering - Special issue: Selected papers from the 30th international conference on computers; industrial engineering
IEEE Transactions on Evolutionary Computation
MDAI '07 Proceedings of the 4th international conference on Modeling Decisions for Artificial Intelligence
Computers and Industrial Engineering
Robust supply chain design under uncertain demand in agile manufacturing
Computers and Operations Research
A memetic algorithm for bi-objective integrated forward/reverse logistics network design
Computers and Operations Research
Computers and Industrial Engineering
Review article: A review of soft computing applications in supply chain management
Applied Soft Computing
Supplier selection for a newsboy model with budget and service level constraints
ICCSA'07 Proceedings of the 2007 international conference on Computational science and its applications - Volume Part I
Advances in Engineering Software
Computers and Industrial Engineering
International Journal of Bio-Inspired Computation
Computers and Industrial Engineering
Optimizing replenishment polices using Genetic Algorithm for single-warehouse multi-retailer system
Expert Systems with Applications: An International Journal
Network optimization in supply chain: A KBGA approach
Decision Support Systems
Credibility-based fuzzy mathematical programming model for green logistics design under uncertainty
Computers and Industrial Engineering
Expert Systems with Applications: An International Journal
Multi-objective no-wait hybrid flowshop scheduling problem with transportation times
International Journal of Computational Science and Engineering
Computers and Industrial Engineering
Computers and Operations Research
Journal of Computational Electronics
Multi-objective optimization of stochastic disassembly line balancing with station paralleling
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
Solving a reverse supply chain design problem by improved Benders decomposition schemes
Computers and Industrial Engineering
Information Sciences: an International Journal
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Supply chain network (SCN) design is to provide an optimal platform for efficient and effective supply chain management. It is an important and strategic operations management problem in supply chain management, and usually involves multiple and conflicting objectives such as cost, service level, resource utilization, etc. This paper proposes a new solution procedure based on genetic algorithms to find the set of Pareto-optimal solutions for multi-objective SCN design problem. To deal with multi-objective and enable the decision maker for evaluating a greater number of alternative solutions, two different weight approaches are implemented in the proposed solution procedure. An experimental study using actual data from a company, which is a producer of plastic products in Turkey, is carried out into two stages. While the effects of weight approaches on the performance of proposed solution procedure are investigated in the first stage, the proposed solution procedure and simulated annealing are compared according to quality of Pareto-optimal solutions in the second stage.