A Decision Framework for Solar PV Panels Supply Chain in Context of Sustainable Supplier Selection and Order Allocation

Sustainable supplier selection and order allocation (SSSOA) is paramount to sustainable supply chain management. It is a complex multi-dimensional decision-making process augmented with the triple bottom line of sustainability. This research presents a multi-phase decision framework to address a SSSOA problem for the multi-echelon renewable energy equipment (Solar PV Panels) supply chain. The framework comprises of fuzzy Multi-Criteria Decision-Making techniques augmented with fuzzy multi-objective mixed-integer non-linear programming mathematical model. The various economic, environmental, and social objectives were optimized for a multi-period, multi-modal transportation network of the supply chain. The results show that among the various sustainable criteria selected in this study, product cost, environmental management system, and health and safety rights of employees are the most important for decision-makers. The results of the mathematical model highlighted the impact of multimodal transportation on overall cost, time, and environmental impact for all periods. An analysis of results revealed that transfer cost and customer clearance cost contribute significantly towards overall cost. Furthermore, defect rate was also observed to play a critical role in supplier selection and order allocation.

A Hybrid Model for Green Supplier Selection and Order Allocation: DEMATEL, ANP, and Multi-criteria Goal Programming Approach

Increased competition in the industrial world forces companies to increase their competitiveness through Green Supply Chain Management (GSCM). The key to the success of GSCM is the selection of suppliers and the allocation of the proper order by taking into account environmental aspects. This decision involves several criteria and must also pay attention to the relationship between criteria. This study proposes a hybrid procedure to solve Green Supplier Selection and Order Allocation (GSSOA). The integration of Decision Making Trial and Evaluation Laboratory (DEMATEL), Analytic Network Process (ANP), and Multi-Criteria Goal Programming (MCGP) are proposed to solve this problem. The DEMATEL is used to calculate the relationship between criteria. Furthermore, the ANP is proposed to determine the weight of the criteria and supplier ranking. Finally, the MCGP method is offered for allocating orders based on priority suppliers. A case study on the food industry in Malang, Indonesia, was conducted to apply this procedure. The results showed that the low defects rate criterion is the most important compared to other criteria. The best supplier was successfully selected, and the order allocation was completed. Order allocation priority is to suppliers D, C, A, and B. This study also presents a sensitivity analysis for order allocation.

An integrated approach based on the decision-theoretic rough set for resilient-sustainable supplier selection and order allocation

PurposeThe purpose of this paper is to propose an innovative integration method based on decision-theoretic rough set and the extended VlseKriterijuska Optimizacija I Komoromisno Resenje (VIKOR) methods to address the resilient-sustainable supplier selection and order allocation (SS/OA) problem.Design/methodology/approachSpecifically, a two-stage approach is designed in this paper. First, the decision-theoretic rough set is employed to calculate the rough number for coping with the subjective uncertainty of data and assigning the weights for a resilient-sustainable evaluation criterion. On this basis, the supplier resilient-sustainable performance is ranked in combination with the extended VIKOR method. Second, a novel multi-objective optimization model is proposed that applies an improved genetic algorithm to select the resilient-sustainable supplier and allocate the corresponding order quantity under a multi-tier supplier network.FindingsThe results reveal that joint consideration of resilience and sustainability is essential in the SS/OA process. The method proposed in this study based on decision-theoretic rough sets and the extended VIKOR method can handle imprecise information flexibly, reduce information loss and obtain acceptable solutions for decision-makers. Numerical cases validate that this integrated approach can combine resilience and sustainability for effective and efficient SS/OA.Practical implicationsThis paper provides industry managers with a new perspective on SS/OA from a resilience and sustainability perspective as a basis for best practices for industry resilience and sustainability. The proposed method helps to evaluate the resilient-sustainable performance of potential suppliers, which is applicable to solving real-world SS/OA problems and has important practical implications for the resilient-sustainable development of supply chains.Originality/valueThe two interrelated priorities of resilience and sustainability have emerged as key strategic challenges in SS/OA issues. This paper is the first study of this issue that uses the proposed integrated approach.

Uncertain Optimization of Discrete Supply Networks with Order Delivery Disruption and Risk Preference in the Postepidemic Era

Epidemic blockade leads to increased uncertainty and dynamic supply network disruption. This study considers an uncertain optimization of dynamic supply networks with risk preference and order delivery disruption. Taking the subjective utility of downstream enterprises as a reference point for the utility measurement of order delivery disruption and risk preference, this study constructs a biobjective optimization model with the goal of maximizing the downstream firm’s subjective utility and minimizing the manufacturer’s cost. The influence of each parameter in the downstream firm’s subjective utility function on the integrated optimization was analysed. The research found that the uncertain optimization model with the risk preference of downstream firms for order delivery disruption better controls the actual manufacturer’s order allocation and distribution problems when considering the downstream firms’ behaviour preference characteristics under bounded rationality. When allocating orders, manufacturers should consider that changes in order delivery disruption will cause changes in the subjective utility of downstream enterprises. In the process of multiperiod cooperation between manufacturers and downstream firms, they can obtain downstream firm risk preferences through repeated investigations.