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 (EctGA) 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.