Exploiting metaheuristics to strategize on performance-based logistics contracts for MRO services

• Main Authors: SCHIRRMANN, Arnd, WONG, Elaine, ZHENG, Zhichao
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2010
• Subjects: Business Administration, Management, and Operations; Strategic Management Policy
• Online Access: https://ink.library.smu.edu.sg/lkcsb_research/5263; https://ink.library.smu.edu.sg/context/lkcsb_research/article/6262/viewcontent/SA_for_MRO_PBC__1_.pdf
• Institution: Singapore Management University

An inherent challenge of using Performance-Based Logistics (PBL) contracts for aircraftmaintenance, repair and overhaul (MRO) services is pricing. As with traditional bricks andmortar services, under-priced contracts cannot cover costs, while overpriced contracts loseout to competition. Furthermore MRO services have an additional element of uncertainty.Performance uncertainties arise due to the inability to accurately forecast demand of spareparts, while cost uncertainties are a result of globally distributed operations subjected tofluctuating economic conditions. Previous work to solve this contracting problem adoptedthe principal-agent model, obtaining an optimal solution from the perspective of both riskaverseparties (i.e., a price-sensitive customer and a profit-driven service provider). Thiswork presents a model that extends existing models by incorporating integrality constraints.Using the metaheuristics, Simulated Annealing algorithm, we show how the new non-linearmixed integer programming model can be efficiently solved by implementing appropriatealgorithms for (a) initial solution derivation, (b) next solution (neighbour) generation, and(c) worse solution acceptance criterion. The algorithm has been tested with real operationaldata and a graphical representation of the results will be provided and analyzed.