Multi-objective particle swarm optimization algorithm for scheduling in flowshops to minimize makespan, total flowtime and completion time variance

Abstract

The present work deals with the development of particle swarm optimization algorithm to solve the multi-objective flowshop scheduling problem. In this paper, minimization of makespan, total flowtime and completion time variance are considered simultaneously. Performance of the proposed methodology has been tested by solving benchmark scheduling problems available in the literature. The proposed methodology is guided to search a set of non-dominated solutions close to the Pareto front. The search capability of the proposed PSO algorithm is enhanced using a local search mechanism. This work is a preliminary step in our research to identify the reference or Pareto solution sets for the benchmark FSPs proposed in the literature, when (C <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">max</sub> ), (tft) and (ctv) are to be simultaneously optimized.