Reverse production systems are often comprised of several tiers with independent members competing at each tier. This research develops and designs a decision-making process for decentralized reverse production systems where each participant in the network determines its decisions in a self-interested way. This dissertation includes three major parts. The first part develops a prototype model for a decentralized reverse production system with two tiers, collectors and processors, focusing on the coordination of transactions of recycled items between these two tiers. The collectors determine the individual material flow allocation mechanisms, based on predictions of the range of prices from the processors, that relate the flow amount to the overall vector of acquisition prices that will be offered by the processors to all the collectors. The processors compete for the flow from the collectors and reach an equilibrium state where no entity is willing to change its decisions. In the second part, we extend the prototype model for a general multi-tiered recycling network comprised of the upstream boundary tier, several intermediate tiers, and the downstream boundary tier where each of the tiers has multiple independent entities. Recycled items flow from the top tier to the downstream tier, but acquisition prices are set from the downstream tier back to the upstream tier. Finally the third part provides a comparison of centralized and decentralized models for reverse production systems and addresses several numerical insights of different system subsidy schemes.

A Reverse Production System (RPS) is a network of transportation logistics and processing functions that collects, refurbishes, and demanufactures for reuse/recycle used or end-of-life products. In this thesis, I focus on the RPS strategic decisions of a processor and collectors when the collection network and contracts for materials can be co-designed. The research problem is motivated by the need of material processors to ensure a consistent flow of material from collectors at a cost that will enable them to be competitive with virgin raw materials. The failure to develop a cost-effective collection network can lead to poor overall economics where expensive processing assets are not fully utilized. The three key problems from the processor s point of view are: 1) how to design a strategic collection network; 2) how to be competitive in the collected materials market place when significant investment is at risk; and 3) how to avoid overpaying for materials when collectors are in regions with different volumes and costs. The multiple goals of this research are: 1) to integrate the contract and strategic network design in RPS; 2) to develop contract mechanism designs to improve the performance under incomplete information and study the value of information (complete vs. incomplete); and 3) to introduce and analyze new strategic network models for effectiveness in solution quality and time. Concepts of mathematical optimization, contract theory, and game theory are utilized in proposing models that couple contract and network problems, including lump sum and variable volume contracts.