Research into developing intelligent sustainable supplier selection and order allocation using multi-agent systems in a partnership supply chain

The supplier selection problem is proven to be one of the most important and popular problems in the research domain of supply chain management. The number of research papers published in the area of traditional supplier selection is abundant with attention focused on considering the most important criteria such as price, quality and service. These approaches demonstrated to be competitive and practical until the emergence of the sustainability issues which has drawn the attentions of mangers and CEOs to incorporate sustainability in all aspects of their manufacturing and supply chain activities. Achieving environmental and sustainable performance within an organization’s supply chain and manufacturing operations will be feasible if upstream supply partners have the same commitments in performing their operations in a sustainable manner. In order to achieve sustainability in manufacturing operations, sustainability needs to be incorporated in all stages of an organization’s supply chain. One aspect of sustainable manufacturing includes the manufacturing of sustainable products in which procurement of sustainable components by eligible suppliers plays an important role. Recently, green/sustainable supplier evaluation and selection has achieved a considerable amount of attentions among researchers. Moreover, allocating optimal order quantities to sustainable suppliers has also attracted attentions of many scholars and industrial practitioners which has not been comprehensively addressed. In order to address these gaps in sustainable supplier selection and order allocation (SSS&OA) problem research domain, the work in this thesis is separated in three major parts. In the first part, evaluation methodologies have been developed to assist a typical manufacturing organization to conduct a comprehensive sustainable assessment of their suppliers. The developed assessment methodologies have been implemented in real world case studies to prove their applicability and efficiency. In the second part, the evaluation scores of the selected sustainable suppliers are then utilized by a proposed bi-objective order allocation model in order to make sourcing decisions. The developed model has been validated through a case study in automotive spare part industry. By investigating further in the buyer-supply relationships, the literature suggests that proper communication and structured information exchange are important components in establishing a long-term partnership and maintaining such a relationship. Toward this end, a Multi-Agent System (MAS) approach has been proposed as a mean of automating and facilitating the process of supplier evaluation and order allocation resulting in a more co-operative partnership. The prototype realization of the proposed MAS approach has been developed and tested using two experiments which prove the capability and applicability of the proposed MAS for the SSS&OA problem. In general, our study contributes to the sustainable supply chain (SC) and operations management literatures by quantitatively investigating the effects of integrating environmental and social sustainability into the process of supplier selection and order allocation. This research shows that financial performance of manufacturing companies adopting environmental and social sustainability in their operations strategy enhanced their competitive advantage that can lead to long-term sourcing relationships for the buyer-supplier dyad. Additionally, it was also shown that applying MASs to the SSS&OA problem can be utilized as an approach to facilitate communications and automate information exchange processes in SCs where suppliers and manufacturer are looking to maintain a long-term SC partnership.