Abstract
This paper presents a joint optimization of the supply chain network in which supplier selection, lateral transshipment, and vehicle routing are involved. Separate consideration of these decisions involved probably offers only poor-quality local optimal solutions. The contribution of this paper is to study the cost minimization of the supply chain network involving the three decisions simultaneously, using both vertical and preventive lateral transshipment, and considering both single objective and multi-objective approach with the following objectives: a minimize the total ordering cost incurred by the wholesaler, b maximize the amount of savings on the different products, and c find the best sequence for delivering various kinds of products to different retailers. A stochastic search technique called fuzzy logic guided genetic algorithms FLGA is proposed to solve the problems. In order to demonstrate the effectiveness of the FLGA, several search methods are compared with the FLGA through simulations in the single objective approach. In the multi-objective approach, two multi-objective evolutionary algorithms entitled Nondominated Sorting Genetic Algorithms 2 NSGA2 and Strength Pareto Evolutionary Algorithm 2 SPEA2 are adopted for comparison with the FLGA. Results show that the FLGA outperforms others in all three considered scenarios for both single objective and multi-objective approaches.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.