Browsing by Author "Ammons, Jane C."

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Centralized versus decentralized decision-making for recycled material flows
(2008-02-15)
Hong, I-Hsuan
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Ammons, Jane C.
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Realff, Matthew J.
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工業工程與管理學系
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Department of Industrial Engineering and Management
A reverse logistics system is a network of transportation logistics and processing functions that collect, consolidate, refurbish, and demanufacture end-of-life products. This paper examines centralized and decentralized models of decision-making for material flows and associated transaction prices in reverse logistics networks. We compare the application of a centralized model for planning reverse production systems, where a single planner is acquainted with all of the system information and has the authority to determine decision variables for the entire system, to a decentralized approach. In the decentralized approach, the entities coordinate between tiers of the system using a parametrized flow function and compete within tiers based on reaching a price equilibrium. We numerically demonstrate the increase in the total net profit of the centralized system relative to the decentralized one. This implies that one may overestimate the system material flows and profit if the system planner utilizes a centralized view to predict behaviors of independent entities in the system and that decentralized contract mechanisms will require careful design to avoid losses in the efficiency and scope of these systems.
Decentralized decision-making and protocol design for recycled material flows
(2008-12-01)
Hong, I-Hsuan
;
Ammons, Jane C.
;
Realff, Matthew J.
;
工業工程與管理學系
;
Department of Industrial Engineering and Management
Reverse logistics networks often consist of several tiers with independent members competing at each tier. This paper develops a methodology to examine the individual entity behavior in reverse production systems. We consider two tiers in the network, collectors and processors. The collectors determine individual flow functions that relate the flow they provide each processor to the overall vector of prices that the processors determine. Because the exact final prices are unknown, each collector solves a robust optimization formulation where the prices paid by the processors are assumed to be within given ranges. The processors compete for the flow from the collectors until the Nash equilibrium is reached in this competitive tier, which sets the vector of prices to be offered to the collectors. To demonstrate the approach, a numerical example is given for a prototypical recycling network. (C) 2008 Elsevier B.V. All rights reserved.