Designing a collaborative supply-chain plan using the analytic hierarchy process and genetic algorithm with cycle-time estimation

Abstract

Collaboration management has become a key issue for supply-chain management and can improve the overall production/manufacturing performance and value. This paper aims to conduct collaborative supply-chain planning and establish supplier selection, as well as production and distribution planning. This study uses an Analytic Hierarchy Process with Rough Sets Theory to establish a supplier purchasing value rating system. Also, a cycle-time estimation procedure is developed to effectively estimate the operating time of a collaborative supply chain. Assembly-line balancing technology is also introduced to guarantee smooth production and distribution in a supply chain. A multi-objective optimisation mathematical model, including purchasing value, cost, cycle time, and smoothness index, is constructed to complete the supplier selection and production-distribution planning. To efficiently solve this mathematical model, this paper proposes a genetic algorithm (E_ctGA) combined with a cycle-time estimation procedure. Finally, it presents a case study for validation. The results show that a better collaborative supply chain plan could be achieved by combining the proposed cycle-time estimation procedure.

Keywords:

• collaborative supply chain
• cycle-time estimation
• assembly-line balancing technology
• analytic hierarchy process
• genetic algorithm

Acknowledgements

The authors would like to thank Miss Y.T. Chen for collecting the data and the National Science Council of Taiwan Government for financial support under Contract No. NSC 98-2410-H-027-002-MY2. We also wish to thank the Editor-in-Chief and the anonymous referees for their valuable comments.