The constrained-collaboration algorithm for intelligent resource distribution in supply networks. (November 2017)

• Record Type: Journal Article
• Authors: Scavarda, Manuel; Seok, Hyesung; Nof, Shimon Y.
• Is Part Of: Computers & industrial engineering. Volume 113(2017)
• Page Start: 803
• Page End: 818
• Publication Date: 2017-11
• Subjects: Collaborative control theory -- Collaborative supply networks -- Decisions networks -- Logistics -- Procurement management; Engineering -- Data processing -- Periodicals; Industrial engineering -- Periodicals; 620.00285
• DOI: 10.1016/j.cie.2017.05.015
• Languages: English
• ISSNs: 0360-8352

Abstract

Highlights: We develop the Constrained-Collaboration Algorithm (CCA) for resource distribution. The CCA is based on Collaborative Control Theory (CCT) and network flow approach. We apply the CCA model to an actual industry case, and show the improvement. We evaluate the performance of our model in terms of resource utilization and cost. Abstract: Manufacturing and supply strategies have evolved from the notion of mass production focusing on economies of scale, to flexible production systems seeking economies of scope, and recently, to the concept of enterprise and supply networks aiming for economies of collaboration. The emergence of supply networks poses new challenges derived from a growing complexity in coordinating the flow of resources, materials, and information within and among an increasing number of network participants. In such situations, an intelligent resource distribution under various constraints is one of the most critical problems. In this paper, we have developed a novel Constrained-Collaboration Algorithm (CCA) for physically cooperative resource distribution planning. Based on Collaborative Control Theory (CCT) with theoretical formulations and network flow approaches, the CCA addresses an efficient and effective resource distribution by a suitable form of physical cooperation. We have applied it to an actual industry case, in combination with Direct/Indirect Delivery Protocol (DIDP), introduced in previous research. As a result, the integrated model achieves 55% increase in resource utilization and 20% reduction in distribution cost, while accommodating external changes. Besides, the new formalism of the physical dimension of collaboration requirement planning introduced in this research with new CCA approach can be generalized for other improvements in supply-and-demand management decision support.