A Modified Invasive Weed Optimization Algorithm for MultiObjective Flexible Jobe Shop Scheduling Problems

Abstract

In this paper, a modified invasive weed optimization (IWO) algorithm is presented for optimization of multiobjective flexible job shop scheduling problems (FJSSPs) with the criteria to minimize the maximum completion time (makespan), the total workload of machines and the workload of the critical machine. IWO is a bio-inspired metaheuristic that mimics the ecological behaviour of weeds in colonizing and finding suitable place for growth and reproduction. IWO is developed to solve continuous optimization problems that's why the heuristic rule the Smallest Position Value (SPV) is used to convert the continuous position values to the discrete job sequences. The computational experiments show that the proposed algorithm is highly competitive to the state-of-the-art methods in the literature since it is able tofind the optimal and best-known solutions on the instances studied.

Review on flexible job shop scheduling

“…Gong et al [137] designed an MA with a well-designed chromosome encoding/decoding method to solve the MOFJSP whose objective is to minimise the maximum completion time, the maximum workload of machines and the total workload of all machines. Mekni and Fayech [138] used a modified invasive weed optimisation algorithm to solve the MOFJSP with three criteria to minimise the makespan, the total workload of machines and the workload of the critical machine. Karthikeyan et al [139] developed a hybrid discrete firefly algorithm combined with local search to solve the MOFJSP with objectives of minimising the maximum completion time, the workload of the critical machine and the total workload of all machines.…”

Resolving of optimal fractional PID controller for DC motor drive based on anti-windup by invasive weed optimization technique

“…Over the specified area the seeds finite number are being spread, any seed produce a new weed and then the weed will produce other weeds from its seeds based on its fitness. The computational experiments show that the IWO is a highly competitive property where it is able to find the best and optimal solutions for the instances studied [20,21].…”

An ingenious invasive weed optimization (IWO) aided maximum power tracking for partially shaded photovoltaic array

“…Invasive weed optimization (IWO) calculation presented by Mehrabian and Lucas in 2006 [29] known for its less parameter taking care of search checks and incredible robustness. IWO has rendered its hand to take care of different building issues like economic load dispatch [30], orientation and designing of antennas [31], and nonstop enhancement issues, for example, non-linear [32] and discrete issues, for example, multi-objective adaptable issues [33]. According to author's learning, it is deduced from the broadwriting overview that there is no evidence of utilizing this strong meta-heuristic IWO calculation for MPPT.…”