A Multiobjective State Transition Algorithm for Single Machine Scheduling

TL;DR

This paper introduces a discrete state transition algorithm for multiobjective single machine scheduling, utilizing non-dominated sorting and Pareto archiving to efficiently find optimal solutions.

Contribution

It presents a novel multiobjective state transition algorithm with non-dominated sorting and Pareto archiving for improved scheduling solutions.

Findings

Demonstrates effectiveness over enumeration and heuristics

Achieves high-quality Pareto solutions

Shows promising results in scheduling optimization

Abstract

In this paper, a discrete state transition algorithm is introduced to solve a multiobjective single machine job shop scheduling problem. In the proposed approach, a non-dominated sort technique is used to select the best from a candidate state set, and a Pareto archived strategy is adopted to keep all the non-dominated solutions. Compared with the enumeration and other heuristics, experimental results have demonstrated the effectiveness of the multiobjective state transition algorithm.