Multiobjective Flexible Job Shop Scheduling Using A Modified Invasive Weed Optimization

摘要

Recently, many studies are carried out with inspirations from ecological phenomena for developingoptimization techniques. The new algorithm that is motivated by a common phenomenon in agriculture iscolonization of invasive weeds. In this paper, a modified invasive weed optimization (IWO) algorithm ispresented for optimization of multiobjective flexible job shop scheduling problems (FJSSPs) with thecriteria to minimize the maximum completion time (makespan), the total workload of machines and theworkload of the critical machine. IWO is a bio-inspired metaheuristic that mimics the ecological behaviourof weeds in colonizing and finding suitable place for growth and reproduction. IWO is developed to solvecontinuous optimization problems that’s why the heuristic rule the Smallest Position Value (SPV) is used toconvert the continuous position values to the discrete job sequences. The computational experiments showthat the proposed algorithm is highly competitive to the state-of-the-art methods in the literature since it isable to find the optimal and best-known solutions on the instances studied