Quantum Particle Swarm Optimization for batch scheduling problem of a single processor in chemical industries

Author

Qi Tang ; Peng Liu ; Xiaoye Zhou ; Chuanbo Li

Author_Institution

Dept. of Logistics Manage., Shenyang Univ. of Technol., Shenyang, China

fYear

2013

fDate

25-27 May 2013

Firstpage

2746

Lastpage

2749

Abstract

In this paper we consider batch scheduling problem of a single processor in chemical industries with precedence constraints to minimize the total weighted tardiness of jobs. This problem is known to be strongly NP-hard. Solution methodologies based on model and Quantum Particle Swarm Optimization (QPSO) are developed to solve it. In this approach, some strategies are designed such as Schedule Generation Scheme (SGS). Computations show that model can obtain 100% optical solutions. QPSO is effective and better than standard PSO and quantum evolution algorithm.

Keywords

batch processing (industrial); chemical industry; constraint theory; particle swarm optimisation; single machine scheduling; NP-hard problem; QPSO; batch scheduling problem; chemical industry; precedence constraint; quantum particle swarm optimization; single processor; total job weighted tardiness; Biological cells; Job shop scheduling; Processor scheduling; Quantum computing; Schedules; Quantum Particle Swarm Optimization; batch scheduling; chemical industries;

fLanguage

English

Publisher

ieee

Conference_Titel

Control and Decision Conference (CCDC), 2013 25th Chinese

Conference_Location

Guiyang

Print_ISBN

978-1-4673-5533-9

Type

conf

DOI

10.1109/CCDC.2013.6561409

Filename

6561409