An Optimised Supplier Selection Plan for Supply Chain Integrated Project Scheduling Problem

Project scheduling (PS) and supply chain management (SCM) are two broad areas that have attracted considerable research attention in recent years. However, the integration of SCM and PS has so far attracted little attention, which motivates this research to include supplier selection strategy in the integrated PS network. Primarily, the project attributes are considered as analogous to the very well-known resource constrained project scheduling problem (RCPSP), which are later integrated with simulated supplier data. After designing mathematical formulations for that integrated model, a genetic algorithm based memetic algorithm (MA) approach is proposed with the objective of minimizing supply chain backward (from supplier to project completion) cost. The proposed algorithm incorporates Nawaz, Enscore, and Ham (NEH) heuristic-based initialization with carefully designed crossover and local search techniques. An online case study model with simulated supplier attributes is considered and solved efficiently to justify the proposed approach. Finally, validation of the proposed MA has been carried out through comparison with a selected state-of-the-art algorithm.