A cooperative game approach to uncertain decentralized logistic systems subject to network reliability considerations

• Published in: Kybernetes Vol. 46; no. 8; pp. 1452 - 1468
• Main Authors: Heidari Gharehbolagh, Hadi, Hafezalkotob, Ashkan, Makui, Ahmad, Raissi, Sadigh
• Format: Journal Article
• Language: English
• Published: London Emerald Publishing Limited 04.09.2017; Emerald Group Publishing Limited
• Subjects: Applied mathematics; Cost allocation; Decision making; Distribution management; Game theory; Leadership; Logistics; Mathematical programming; Network reliability; Parameter sensitivity; Players; Reliability analysis; Sensitivity analysis; Water distribution; Water engineering; Logistic network; Maximum-flow; Reliability; Decentralized network; Cooperative game
• ISSN: 0368-492X; 1758-7883
• DOI: 10.1108/K-02-2017-0043

Purpose Maximum-flow of an uncertain multi-owner network has become very important recently. This study aims to evaluate the maximum flow on a cooperated logistic system in the presence of uncertainties, raised by travel time, capacity, cost and failures. Design/methodology/approach To consider different uncertainties and to promote network efficiency, the proposed model is enriched with a cooperative game methodology and a reliability method. A scenario-based method covers optimistic, pessimistic and most likely estimates time, cost and capacity of each route as well as applies a prior failure pattern for breakdown of any resource. Findings A linear optimization model, which is enriched with target reliability estimation, is presented. Results on a water distribution network indicate more revenue performance for players. Carrying out sensitivity analysis shows the importance of the model parameters. Originality/value Modeling maximum-flow problem in the presence of many sources of uncertainty with the aim of a cooperative game is the main contribution of the present study. Also, a novel method based on the reliability theory is applied to close the chasm on evaluating the real maximum flow in a shared decentralized network which suffers from risky conditions on arcs and nodes.