An effective PSO-based hybrid algorithm for multiobjective permutation flow shop scheduling

IEEE Transactions on Systems, Man, and Cybernetics Part A:Systems and Humans

Volumn 38, Issue 4, 2008, Pages 818-831

  Li, Bin Bin ^a   Wang, Ling ^a   Liu, Bo ^a  

^a TSINGHUA UNIVERSITY   (China)

Author keywords

Adaptive meta Lamarckian learning; Hybrid algorithm; Local search; Multiobjective optimization (MOO); Pareto front; Particle swarm optimization (PSO); Permutation flow shop scheduling

Indexed keywords

ADAPTIVE ALGORITHMS; ANNEALING; BOOLEAN FUNCTIONS; CIRCUIT THEORY; COMBINATORIAL MATHEMATICS; COMBINATORIAL OPTIMIZATION; EVOLUTIONARY ALGORITHMS; FUNCTION EVALUATION; HEURISTIC PROGRAMMING; MACHINE SHOP PRACTICE; MATHEMATICAL TRANSFORMATIONS; NUCLEAR PROPULSION; OPTIMIZATION; PARALLEL ALGORITHMS; PARTICLE SWARM OPTIMIZATION (PSO); PROBLEM SOLVING; RANDOM PROCESSES; SCHEDULING; SCHEDULING ALGORITHMS; SIMULATED ANNEALING; SOLUTIONS;

APPLIED (CO); COMBINATORIAL OPTIMIZATION PROBLEMS; EVOLUTION PROCESSES; HYBRID ALGORITHM (HA); INDIVIDUAL (PSS 544-7); LEARNING STRATEGIES; LOCAL SEARCH (LS); LOCAL SEARCH (LS) METHODS; MULTI OBJECTIVE ALGORITHMS; MULTI OBJECTIVES; MULTIPLE OBJECTIVES; NP-HARD; PARALLEL EVOLUTION; PARETO FRONTS; PARTICLE SWARM OPTIMIZATION (PSO); PERMUTATION FLOW-SHOP SCHEDULING; PREMATURE CONVERGENCE; RULE BASE (IF THEN); SCHEDULING PROBLEMS; SEARCHING BEHAVIOR; SEARCHING DIRECTION; SIMULATION RESULTS;

MULTIOBJECTIVE OPTIMIZATION;

EID: 46649103641     PISSN: 10834427     EISSN: None     Source Type: Journal    
DOI: 10.1109/TSMCA.2008.923086     Document Type: Article

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