A simulator that uses Tabu search to approach the optimal solution to stochastic inventory models
Computers and Industrial Engineering
Simulation optimization using tabu search
Proceedings of the 32nd conference on Winter simulation
Multiobjective Scheduling by Genetic Algorithms
Multiobjective Scheduling by Genetic Algorithms
Computer Simulation in Management Science
Computer Simulation in Management Science
Introduction to Simulation Using SIMAN
Introduction to Simulation Using SIMAN
Dissipative particle swarm optimization
CEC '02 Proceedings of the Evolutionary Computation on 2002. CEC '02. Proceedings of the 2002 Congress - Volume 02
An Improved Particle Swarm Optimization with Mutation Based on Similarity
ICNC '07 Proceedings of the Third International Conference on Natural Computation - Volume 04
Network Models and Optimization: Multiobjective Genetic Algorithm Approach
Network Models and Optimization: Multiobjective Genetic Algorithm Approach
Intelligent and Evolutionary Systems
Intelligent and Evolutionary Systems
Advanced Engineering Informatics
Ordinal optimization based approach to the optimal resource allocation of grid computing system
Mathematical and Computer Modelling: An International Journal
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Assembly line design is an important part of production system. Some processes need to undergo changes in order to increase in efficiency. Computer simulation has been applied on process design for many decades. Traditionally, simulation had to run all possible alternatives of assembly line and was not considered as an optimization technique. Thus, this study employs particle swarm optimization (PSO) algorithm which is with mutation based on similarity for simulation optimization in order to optimize the managerial parameters in production system. Through experimentation designs and statistics tests, the simulation results show that the proposed method is better than other algorithms, like genetic algorithm and conventional PSO algorithm for solving assembly line design problem.