Optimization Models for Multiple Resource Planning

Abstract

Multiple resource planning is a very crucial undertaking for most organizations. Apart from reducing operational complexity, multiple resource planning facilitates efficient allocation of resources which reduces costs by minimizing the cost of tardiness and the cost for additional capacity. The current research investigates multiple resource loading problems (MRLP). MRLPs are very prevalent in today's organizational environments and are particularly critical for organizations that handle concurrent, time-intensive, and multiple-resource projects. Using data obtained from the Ministry of Administrative Development, Labor and Social Affairs (ADLSA), an MRLP is proposed. The problem utilizes data regarding staff, time, equipment, and finance to ensure efficient resource allocation among competing projects. In particular, the thesis proposes a novel model and solution approach for the MRLP. Computational experiments are then performed on the model. The results show that the model performs well, even in higher instances. The positive results attest to the effectiveness of the proposed MRLP problem