Abstract
In this paper, an enhanced version of the Bees Algorithm is proposed in dealing with multi-objective supply chain model to find the optimum configuration of a given supply chain problem in order to minimise the total cost and the total lead-time. The new Bees Algorithm includes an adaptive neighbourhood size change and site abandonment (ANSSA) strategy which is an enhancement to the basic Bees Algorithm. The supply chain case study utilised in this work is taken from literature and several experiments have been conducted in order to show the performances, the strength, the weaknesses of the proposed method and the results have been compared to those achieved by the basic Bees Algorithm and Ant Colony optimisation. The results show that the proposed ANSSA-based Bees Algorithm is able to achieve better Pareto solutions for the supply chain problem.
| Original language | English |
|---|---|
| Pages (from-to) | 71-82 |
| Number of pages | 12 |
| Journal | Swarm and Evolutionary Computation |
| Volume | 18 |
| Early online date | 26 Apr 2014 |
| DOIs | |
| Publication status | Published - Oct 2014 |
Keywords
- Adaptive neighbourhood search
- Bees Algorithm
- Multi-objective optimisation
- Site abandonment
- Supply chain management
- Swarm-based optimisation
ASJC Scopus subject areas
- Computer Science(all)
- Mathematics(all)