A Lagrangian heuristic for integrated production planning, material ordering and investment multi-project scheduling in a project-driven supply chain

Abstract

Effective decision making in large project planning presents a significant challenge. Despite progress in developing mathematical models, few studies comprehensively address project and supply-chain management aspects in an integrated framework. This article presents an integrated approach for multi-project resource investment, material ordering and production planning in a project-driven supply chain. A mixed-integer programming model is developed to optimize the total cost of renewable resource investment, production, transportation, and material ordering and holding, with an opportunity to share mobile renewable resources across multiple projects. A Lagrangian relaxation heuristic algorithm is proposed to determine the upper and lower bounds for the objective function, with an additional set of valid cuts to reduce the distance between bounds. The results of numerical experiments demonstrate the favourable performance of the proposed algorithm compared to the GAMS solver. This article provides insights into supply-chain participant expenses and activity scheduling based on these findings.