Optimization of control parameters for genetic algorithms
IEEE Transactions on Systems, Man and Cybernetics
Simulated annealing: theory and applications
Simulated annealing: theory and applications
Modern heuristic techniques for combinatorial problems
Modern heuristic techniques for combinatorial problems
Genetic algorithms + data structures = evolution programs (3rd ed.)
Genetic algorithms + data structures = evolution programs (3rd ed.)
A tabu search heuristic for the multi-depot vehicle routing problem
Computers and Operations Research
Fuzzy logic: intelligence, control, and information
Fuzzy logic: intelligence, control, and information
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Tabu Search
Iterative Computer Algorithms with Applications in Engineering: Solving Combinatorial Optimization Problems
Multi-Objective Optimization Using Evolutionary Algorithms
Multi-Objective Optimization Using Evolutionary Algorithms
An analysis of the behavior of a class of genetic adaptive systems.
An analysis of the behavior of a class of genetic adaptive systems.
A New Decision Rule for Lateral Transshipments in Inventory Systems
Management Science
Information Sciences: an International Journal
Multi-objective Supply Chain Optimization: An Industrial Case Study
Proceedings of the 2007 EvoWorkshops 2007 on EvoCoMnet, EvoFIN, EvoIASP,EvoINTERACTION, EvoMUSART, EvoSTOC and EvoTransLog: Applications of Evolutionary Computing
Natural and simulated annealing
Computing in Science and Engineering
A fast and elitist multiobjective genetic algorithm: NSGA-II
IEEE Transactions on Evolutionary Computation
Handling multiple objectives with particle swarm optimization
IEEE Transactions on Evolutionary Computation
IEEE Transactions on Evolutionary Computation
AbYSS: Adapting Scatter Search to Multiobjective Optimization
IEEE Transactions on Evolutionary Computation
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Interactive Particle Swarm: A Pareto-Adaptive Metaheuristic to Multiobjective Optimization
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
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This paper presents a joint optimization of the supply chain network in which supplier selection, lateral transshipment, and vehicle routing are involved. Separate consideration of these decisions involved probably offers only poor-quality local optimal solutions. The contribution of this paper is to study the cost minimization of the supply chain network involving the three decisions simultaneously, using both vertical and preventive lateral transshipment, and considering both single objective and multi-objective approach with the following objectives: a minimize the total ordering cost incurred by the wholesaler, b maximize the amount of savings on the different products, and c find the best sequence for delivering various kinds of products to different retailers. A stochastic search technique called fuzzy logic guided genetic algorithms FLGA is proposed to solve the problems. In order to demonstrate the effectiveness of the FLGA, several search methods are compared with the FLGA through simulations in the single objective approach. In the multi-objective approach, two multi-objective evolutionary algorithms entitled Nondominated Sorting Genetic Algorithms 2 NSGA2 and Strength Pareto Evolutionary Algorithm 2 SPEA2 are adopted for comparison with the FLGA. Results show that the FLGA outperforms others in all three considered scenarios for both single objective and multi-objective approaches.