Authors:
Souad Mekni
;
Besma Fayech Char
and
Mekki Ksouri
Affiliation:
ACS, Ecole Nationale d.Ingnieurs de Tunis, Tunisia
Keyword(s):
Flexible Job Shop Scheduling, Multiobjective Optimization, Particle Swarm Optimization, Smallest Position Value.
Related
Ontology
Subjects/Areas/Topics:
Informatics in Control, Automation and Robotics
;
Intelligent Control Systems and Optimization
;
Optimization Algorithms
Abstract:
Because of the intractable nature of the .exible job shop scheduling problem and its importance in both .elds of production management and combinatorial optimization, it is desirable to employ e cient metaheuristics in order to obtain a better solution quality for the problem. In this paper, a novel approach based on the vector evaluated particle swarm optimization and the weighted average ranking is presented to solve .exible job shop scheduling problem (FJSP) with three objectives (i) minimize the makespan, (ii) minimize the total workload of machines and (iii) minimize the workload of critical machine. To convert the continuous position values to the discrete job sequences, we used the heuristic rule the Smallest Position Value (SPV). Experimental results in this work are very encouraging since that relevent solutions were provided in a reasonable computational time.