Thesis (M.Phil.)--City University of Hong Kong, 2009. / "Submitted to Department of Manufacturing Engineering and Engineering Management in partial fulfillment of the requirements for the degree of Master of Philosophy." Includes bibliographical references (leaves 87-91)

Includes bibliographical references (p. 79-84).

Thesis (Ph. D.)--University of Missouri-Columbia, 2003. / Typescript. Vita. Includes bibliographical references (leaves 160-166). Also available on the Internet.

Thesis (M. Phil.)--University of Hong Kong, 2002. / Includes bibliographical references (leaves 275-286).

published_or_final_version / Industrial and Manufacturing Systems Engineering / Doctoral / Doctor of Philosophy

Supplier selection is an important problem in supply chain management (SCM), and has attracted the attention of many researchers. Most previous research on supplier selection is based on the assumption that a single product is required. For the few supplier selection models for multiple products, they handled the problem on a product-by-product manner. In such cases, the synergy effect between products which could impact the choice of cooperative suppliers is not taken into account. However, it is practical for the purchasing company to procure multiple products simultaneously and benefit from the synergy effect between products. It is necessary to incorporate the synergy effect between products in multi-product supplier selection. This thesis presents a multi-product supplier selection model incorporating the synergy effect between products. The model is composed of three sub-models, i.e., the synergy determination sub-model, the supplier pre-selection sub-model and the negotiation-based final selection sub- model. As the agent-based technology is a natural tool for modeling distributed systems, the proposed multi-product supplier selection model is realized as a multi-agent system (MAS) with agents representing the relevant parties and functions of the proposed model. Agents of the MAS are able to interact with each other through the respective agent interaction protocols defined specifically for the three sub-models. The synergy determination sub-model is to determine the synergy effect between products. The term complementarity is used to represent the synergy effect between products. The product complementarity measure criteria are formulated based on the activities of automobile manufacturers. Complementarity measure methods are then proposed. The product bundle determination algorithm is presented to generate preferred product bundles. The interaction of agents involving in the sub-model is governed by the synergy determination protocol. The supplier pre-selection sub-model is to shortlist the qualified and competitive suppliers for multiple products. The pre-selection criteria catering for the multi-product environment are formulated. Both the general characteristics and performances of suppliers, and the capabilities supporting multi-product transactions are included in the pre-selection criteria. The TOPSIS-based supplier pre-selection algorithm is established to evaluate suppliers on these criteria. The interaction of agents involving in the sub-model is governed by the pre-selection protocol. The negotiation-based final selection sub-model is to select the cooperative suppliers for multiple products. In order to cater for the multi-product environment, multiple bids are allowed in the negotiation model. The corresponding bid utility function and negotiation strategies are presented. The B&B-based winner determination algorithm is presented to determine the cooperative suppliers. The hybrid protocol of combinatorial procurement auction and multi-bilateral bargaining is established to govern the interaction of agents in the sub-model. A case study has been executed to demonstrate the feasibility, effectiveness and usefulness of the supplier selection model for multiple products with synergy effect. The results indicate that the proposed supplier selection model is able to select suppliers for multiple products simultaneously and incorporate the synergy effect between products. In addition, the agent interaction protocols and related algorithms used in the agent-based system supporting the multi-product supplier selection model are suitable and effective. / published_or_final_version / Industrial and Manufacturing Systems Engineering / Doctoral / Doctor of Philosophy

To implement green supply chain, a company has to consider sustainability impacts in assessing potential suppliers. Thereby, the supplier evaluation and selection criteria would include various key performance indicators such as price, quality, delivery, as well as environmental and corporate social responsibility aspects. Researchers have proposed numerous multi-criteria decision making (MCDM) approaches for evaluating the multiple conflicting criteria in supplier selection. However, most of the existing approaches have ignored some important issues in business environment such as supplier qualification, supplier autonomy, negotiation between manufacturer and supplier, etc. In this thesis, a multi-agent system (MAS) is proposed for supplier selection in green supply chain. It comprises two types of autonomous agents, namely, buyer agent and seller agents, to represent the interests of manufacturer and suppliers, respectively. The proposed MAS presents three prominent features. First, the proposed supplier selection criteria incorporate the conventional, environmental and social aspects in the supplier selection process. The criteria are classified into negotiable and non-negotiable criteria. Initially, all criteria are included to evaluate and rank all the candidate suppliers. Subsequently, the top-ranked candidates are invited to participate in the bargaining process. In this regard, the negotiable criteria are used for assessing the quality of an offer, while the non-negotiable criteria, i.e. environmental and social criteria, influence the manufacturer’s negotiation attitude to candidate suppliers. The classification enables the manufacturer to fully utilize the performance values of all criteria. Secondly, supplier selection is implemented in a two-stage methodology. The TOPSIS method is devised in the first stage to shortlist some suitable candidate suppliers for entering negotiation in the next stage. In the second stage, the agent-based negotiation process is adopted for selecting the final supplier. Representing the manufacturer and the shortlisted suppliers respectively, the buyer and seller agents bargain on a number of negotiable issues in the multi-round negotiation. A multi-issue and multilateral agent interaction protocol, which is an extension of the contract net protocol, is implemented in the MAS. Accordingly, the buyer agent coordinates with the seller agents to exchange offers and counteroffers. Thirdly, a novel preference-based negotiation strategy is used to govern the behavior of agents during negotiation. A heuristics model with the Particle Swarm Optimization (PSO) algorithm and Adaptive Penalty Function has been designed and implemented to realize the proposed negotiation strategy. The strategy guides the autonomous agents to narrow down the discrepancies in the values of the negotiable criteria (price, delivery days, contract length) in their offers, and simultaneously search a mutually beneficial and acceptable agreement. The negotiation payoffs and negotiation time are improved. Experimental results indicate that the proposed agent-based model could help the manufacturer to identify the most appropriate supplier and improve the quality of final agreement. In addition, the model successfully integrates supplier qualification and automated negotiation, and promotes supplier autonomy in the supplier selection process. / published_or_final_version / Industrial and Manufacturing Systems Engineering / Master / Master of Philosophy

Not available / text

Not available

The dissertation consists of three essays. In the first essay, I analyze the dynamic interactions in a decentralized distribution channel, composed of a manufacturer and a retailer, to launch an innovative durable product (IDP) whose underlying retail demand is influenced by word-of-mouth from past adopters and follows a Bass-type diffusion process. The word-of-mouth influence creates a trade-off between immediate and future sales/ profits, resulting in a multi-period dynamic supply chain coordination problem. The analysis shows that the manufacturer and retailer may have conflicts regarding their trade-offs and preferences between immediate and future profits. I characterize equilibrium pricing strategies and the resulting sales and profit trajectories. Surprisingly, I find that the manufacturer, and sometimes even the retailer, is better off with a myopic retailer strategy in some cases. Furthermore, I propose that revenue sharing contracts can coordinate the IDP supply chain throughout the entire planning horizon. In the second essay, I extend the demand model by considering the impact of shelf space allocation on the retail demand of an IDP. I assume the retail demand to be an increasing and concave function of the merchandise displayed on the shelf. I include a linear cost of shelf space in the retailer's objective function. I characterize the optimal dynamic shelf space allocation and retail pricing policies for the retailer and wholesale pricing policies for the manufacturer. I find that a myopic retailer allocates the constant amount of shelf-space to the IDP over the selling horizon, whereas the shelf space allocated to the IDP by a far-sighted retailer varies over time. Consistent with the first essay, the manufacturer and the retailer have conflict over the retailer's profitability strategy. In the third essay, I review the Stackelberg differential game models that study such issues in dynamic environments as production and inventory policies, outsourcing decisions, channel coordination, and competitive advertising. I introduce the basic concepts of the basics of the Stackelberg differential games. I focus on the models that derive the Stackelberg equilibria in the area of supply chain management and marketing channels.