EconPapers    
Economics at your fingertips  
 

An efficient generalised opposition-based multi-objective optimisation method for factory cranes with time-space constraints

Binghai Zhou and Xiumei Liao

European Journal of Industrial Engineering, 2020, vol. 14, issue 5, 684-714

Abstract: In order to improve the performance of large manufacturing enterprises, besides the adoption of new technologies, it is also feasible to efficiently schedule logistics equipment such as cranes, which costs much less since only software changes are involved. In this research, the objectives of minimising total waiting cost and total delay cost are optimised simultaneously when executing crane-delivery tasks in factories. Given the time-space constraints and NP-hard nature of the problem, a generalised opposition-based learning (GOBL) mechanism and two problem-based searching strategies are developed and fused into the multi-objective differential evolution approach, namely GOMODE. The introduction of GOBL mechanism enables the proposed algorithm to search in a more extensive solution space, which improves the population diversity and avoids the premature problem. The performance of the GOMODE has been compared with classical multi-objective optimisation algorithms. The experimental results indicate that the GOMODE achieves a better performance both on solutions' quality and diversity. [Received: 11 December 2018; Accepted: 23 December 2019]

Keywords: generalised opposition-based learning; GOBL; factory crane scheduling; multi-objective optimisation; time-space constraints. (search for similar items in EconPapers)
Date: 2020
References: Add references at CitEc
Citations: Track citations by RSS feed

Downloads: (external link)
http://www.inderscience.com/link.php?id=109923 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ids:eujine:v:14:y:2020:i:5:p:684-714

Access Statistics for this article

More articles in European Journal of Industrial Engineering from Inderscience Enterprises Ltd
Bibliographic data for series maintained by Sarah Parker ().

 
Page updated 2021-03-06
Handle: RePEc:ids:eujine:v:14:y:2020:i:5:p:684-714