Multi-strategy ensemble artificial bee colony algorithm for large-scale production scheduling problem. (2015)

• Record Type: Journal Article
• Authors: Wang, Hui; Wang, Wenjun; Sun, Hui
• Is Part Of: International journal of innovative computing and applications. Volume 6:Number 3/4(2015)
• Page Start: 128
• Page End: 136
• Publication Date: 2015
• Subjects: artificial bee colony -- ABC -- production scheduling -- flow shop scheduling -- discrete optimisation -- multi-strategy ensemble -- large-scale scheduling -- smallest position value -- simulation; Evolutionary computation -- Periodicals; Neural networks (Computer science) -- Periodicals; Genetic programming (Computer science) -- Periodicals; Biologically-inspired computing -- Periodicals; Swarm intelligence -- Periodicals; Quantum computers -- Periodicals; 006.3
• Languages: English
• ISSNs: 1751-648X

Abstract

This paper presents a multi-strategy ensemble artificial bee colony (MEABC) algorithm for solving large-scale production scheduling problem. MEABC is a new variant of artificial bee colony (ABC), which has shown good performance on many continuous optimisation problems. To apply MEABC to discrete production scheduling problem, the smallest position value (SPV) rule is employed. Moreover, a modified NEH-based population initialisation method is utilised for generating high-quality initial solutions. Experimental study is conducted on a set of 140 flow shop scheduling problems with the size from 20 × 5 to 2, 000 × 100. Simulation results show that MEABC performs better than the NEH and ABC on all test instances.