A Discrete Multi-Objective Rider Optimization Algorithm for Hybrid Flowshop Scheduling Problem Considering Makespan, Noise and Dust Pollution

Yanming Fu,Chiwen Qu,Ningjiang Chen,Zhuohang Li

doi:10.1109/access.2020.2993084

Abstract

Many optimization algorithms have been proposed to solve hybrid flowshop scheduling problem (HFSP). However, with the development of industry and society, labor right and labor safety have become important problem to consider in production scheduling. So the green HFSP considering makespan, noise and dust pollution becomes an urgent problem to be solved. In this paper, the rider optimization algorithm (ROA) is modified into the multi-objective rider optimization algorithm (MOROA) using Pareto archive and neighborhood sorting techniques. The Pareto archive and neighborhood sorting technology make the Pareto optimal solution set of MOROA have higher coverage and more solutions. Then MOROA is discretized into discrete MOROA (DMOROA) to solve the HFSP considering makespan, noise and dust pollution. DMOROA is tested on 10, 30 and 50 jobs HFSP considering makespan, noise and dust pollution. The test results are compared with two multi-objective algorithms to verify the performance of DMOROA. And the test results verify that the DMOROA is superior to the comparison algorithms in search accuracy, number of non-dominated solutions, diversity of solution set and stability. Therefore, DMOROA is effective in solving multi-objective HFSP considering makespan, noise and dust pollution.

Highlights

The hybrid flowshop scheduling problem (HFSP) is a kind of combinatorial optimization problem which integrates the traditional flowshop scheduling and parallel machine scheduling [1]
SIMULATION EXPERIMENT The experiment results of HFSP considering makespan, noise and dust pollution are compared between discrete MOROA (DMOROA), non-dominated sorting genetic algorithm 2 (NSGA2) and multi-objective particle swarm optimization algorithm (MOPSO) to evaluate the performance of DMOROA
This paper studies green HFSP from the perspective of labor right, and proposes a HFSP considering makespan, noise and dust pollution

Summary

INTRODUCTION

The hybrid flowshop scheduling problem (HFSP) is a kind of combinatorial optimization problem which integrates the traditional flowshop scheduling and parallel machine scheduling [1]. Y. Fu et al.: DMOROA for HFSP Considering Makespan, Noise and Dust Pollution algorithm was developed based on constructing heuristic algorithm to solve HFSP with minimum maximum completion time and total flow time. Reference [13] presented a discrete multi-objective firefly algorithm to solve the HFSP considering makespan, total flow time and machine idle time. In reference [14], a multi-objective discrete artificial bee colony algorithm was proposed to solve the green HFSP with the maximum completion time and the minimum total energy consumption. Reference [16] enhanced the multi-objective evolutionary algorithm with problem-specific heuristics to deal with the lot-streaming HFSP This method was a new research direction and close to the reality, yet the algorithm had high time complexity. (6) If at least one machine is available in a stage, the stage shall be started immediately after the completion of the previous stage

DESCRIPTION OF VARIABLES AND SYMBOLS

DEFINITION OF MULTI-OBJECTIVE OPTIMIZATION PROBLEM

POPULATION DISCRETIZATION

SIMULATION EXPERIMENT

Findings

CONCLUSION