Product platform two-stage quality optimization design based on multiobjective genetic algorithm
Computers & Mathematics with Applications
Research on quality performance conceptual design based on SPEA2+
Computers & Mathematics with Applications
Computers & Mathematics with Applications
An effective hybrid optimization approach for multi-objective flexible job-shop scheduling problems
Computers and Industrial Engineering
Evolutionary multi-objective optimization: a historical view of the field
IEEE Computational Intelligence Magazine
Multiobjective evolutionary algorithms: a comparative case studyand the strength Pareto approach
IEEE Transactions on Evolutionary Computation
Multiobjective evolutionary algorithms for electric power dispatch problem
IEEE Transactions on Evolutionary Computation
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This paper presents an Improved Strength Pareto Evolutionary Algorithm 2 (ISPEA2), which introduces a penalty factor in objective function constraints, uses adaptive crossover and a mutation operator in the evolutionary process, and combines simulated annealing iterative process over SPEA2. The testing result of ISPEA2 by authoritative testing functions meets the requirement of Petro-optimum fronts. The case study result shows that the proposed algorithm provides a rapid convergence in obtaining Pareto-optimal solutions during the calculation process of evolution. Based on the fuzzy set theory, ISPEA2 is able to solve the multi-objective problems in the IEEE 33-bus system, and its validity and practicality are demonstrated by the utilization on DG's economic dispatch and optimal operation in the field of power industry.