A hybrid approach for cost-optimized lateral transshipment in a supply chain environment
Abstract
Purpose
When making sourcing decisions, both cost optimization and customer demand fulfillment are equally important for firm competitiveness. The purpose of this paper is to develop a stochastic search technique, hybrid genetic algorithm (HGA), for cost-optimized decision making in wholesaler inventory management in a supply chain network of wholesalers, retailers and suppliers.
Design/methodology/approach
This study develops a HGA by using a mixture of greedy-based and randomly generated solutions in the initial population and a local search method (hill climbing) applied to individuals selected for performing crossover before crossover is implemented and to the best individual in the population at the end of HGA as well as gene slice and integration.
Findings
The application of the proposed HGA is illustrated by considering multiple scenarios and comparing with the other commonly adopted methods of standard genetic algorithm, simulated annealing and tabu search. The simulation results demonstrate the capability of the proposed approach in producing more effective solutions.
Practical implications
The pragmatic importance of this method is for the inventory management of wholesaler operations and this can be scalable to address real contexts with multiple wholesalers and multiple suppliers with variable lead times.
Originality/value
The proposed stochastic-based search techniques have the capability in producing good-quality optimal or suboptimal solutions for large-scale problems within a reasonable time using ordinary computing resources available in firms.
Keywords
Acknowledgements
The authors wish to thank the Australian Research Council for funding support to Drs Nakandala and Lau under the ARC Discovery Grant of DP130101114 and also the Research Office of the Hong Kong Polytechnic University for their support to Dr Ning.
Citation
Nakandala, D., Lau, H. and Ning, A. (2016), "A hybrid approach for cost-optimized lateral transshipment in a supply chain environment", Business Process Management Journal, Vol. 22 No. 4, pp. 860-878. https://doi.org/10.1108/BPMJ-08-2015-0122
Publisher
:Emerald Group Publishing Limited
Copyright © 2016, Emerald Group Publishing Limited