The design and analysis of a computational model of cooperative coevolution
The design and analysis of a computational model of cooperative coevolution
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
An Endosymbiotic Evolutionary Algorithm for Optimization
Applied Intelligence
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Proceedings of the 1st International Conference on Genetic Algorithms
Biases in the Crossover Landscape
Proceedings of the 3rd International Conference on Genetic Algorithms
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Proceedings of the 5th International Conference on Genetic Algorithms
Multi-objective Co-operative Co-evolutionary Genetic Algorithm
PPSN VII Proceedings of the 7th International Conference on Parallel Problem Solving from Nature
A Short Tutorial on Evolutionary Multiobjective Optimization
EMO '01 Proceedings of the First International Conference on Evolutionary Multi-Criterion Optimization
A symbiotic evolutionary algorithm for the integration of process planning and job shop scheduling
Computers and Operations Research
Multileveled Symbiotic Evolutionary Algorithm: Application to FMS Loading Problems
Applied Intelligence
Comparison of Multiobjective Evolutionary Algorithms: Empirical Results
Evolutionary Computation
Evolutionary Algorithms for Solving Multi-Objective Problems (Genetic and Evolutionary Computation)
Evolutionary Algorithms for Solving Multi-Objective Problems (Genetic and Evolutionary Computation)
Muiltiobjective optimization using nondominated sorting in genetic algorithms
Evolutionary Computation
A parametric fuzzy logic approach to dynamic part routing under full routing flexibility
Computers and Industrial Engineering
SPAM: Set Preference Algorithm for Multiobjective Optimization
Proceedings of the 10th international conference on Parallel Problem Solving from Nature: PPSN X
Computers and Industrial Engineering
A fast multi-objective evolutionary algorithm based on a tree structure
Applied Soft Computing
Multiobjective evolutionary algorithms: a comparative case studyand the strength Pareto approach
IEEE Transactions on Evolutionary Computation
A fast and elitist multiobjective genetic algorithm: NSGA-II
IEEE Transactions on Evolutionary Computation
On the Evolutionary Optimization of Many Conflicting Objectives
IEEE Transactions on Evolutionary Computation
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This paper presents an evolutionary algorithm, called the multi-objective symbiotic evolutionary algorithm (MOSEA), to solve a multi-objective FMS process planning (MFPP) problem with various flexibilities. The MFPP problem simultaneously considers four types of flexibilities related to machine, tool, sequence, and process and takes into account three objectives: balancing the machine workload, minimizing part movements, and minimizing tool changes. The MOSEA is modeled as a two-leveled structure to find a set of well-distributed solutions close to the true Pareto optimal solutions. To promote the search capability of such solutions, two main processes imitating symbiotic evolution and endosymbiotic evolution are introduced, together with an elitist strategy and a fitness sharing scheme. Evolutionary components suitable for the MFPP problem are provided. With a variety of test-bed problems, the performance of the proposed MOSEA is compared with those of existing multi-objective evolutionary algorithms. The experimental results show that the MOSEA is promising in solution convergence and diversity.