Circular economy-driven two-stage supply chain management for nullifying waste

In recent years, supplier selection has been significantly important with respect to dimensions and criteria of sustainability. Organizations need to try to choose their suppliers based on how well their performances are in each of the economic, social, and environmental criteria. On the other hand, since the methods of supplier selection depend on the experts’ opinions, which have the potential of uncertainty and ambiguity, using Fuzzy sets to evaluate the criteria can be useful. Apart from considering experts’ opinions on a fuzzy basis, probabilities are considered in experts’ opinions via Z-numbers in order to increase the reliability of the data and the results. In this paper, after reviewing the literature, identifying the sustainability criteria, and step-by-step explaining the presented method, a numerical example is studied for more clarification. Moreover, the results of the conventional fuzzy sets are obtained and have been compared with those considering the probabilities (Z-number) leading to the conclusion that applying the experts’ opinions will be effective in ranking the suppliers.

Sustainable supplier selection by a new possibilistic hierarchical model in the context of Z-information

A parallel-machine scheduling problem with preventive maintenance is studied in the paper Because of the existence of indeterminacy phenomenon, the processing and maintenance time are assume to be uncertain variables To address these uncertain parameters, two pessimistic value mathematical programming models are developed and the equivalence is proved The worst-case bound of longest processing time (LPT) rule for the problem under an uncertain environment is obtained To solve this problem effectively, an improved LPT rule is proposed according to the result of the theoretical analysis Finally, numerical experiments show that the improved LPT outperforms the LPT in improving the quality of the optimal value and has a less relative error than that of the LPT

A parallel-machine scheduling problem with periodic maintenance under uncertainty

In the present study, a two-echelon fixed charge transportation problem is investigated under uncertainty. Due to the existence of considerable amount of uncertainties, the demands, supplies, availabilities, fixed charges and transported quantities in this problem are assumed as uncertain variables. The aim is to maximize the total profit under uncertain environments. The expected value model, chance-constrained model and measure chance model are developed, and the deterministic equivalent forms of these models are obtained by inverse uncertainty distribution. Genetic algorithm and particle swarm optimization are proposed to solve the equivalent forms of the models based on the structure of the problem. To verify the effectiveness of these proposed approaches, numerical experiments are performed.

An uncertain two-echelon fixed charge transportation problem

The purpose of this study is to develop a pragmatic method for managing the inventory and production of blood platelets in places with inappropriate infrastructure. Thus far, we can find a rich number of papers regarding the optimization of blood products supply chain but most of them are impractical due to utilizing so many mathematical formulas and parameters. Hence, as an interdisciplinary study, we should develop a comprehensible method for medical workers and doctors to optimize the supply chain, maintain the quality of services and overcome the challenges. The inventory manager has to cope with multifaceted problems, among those are limited availability of donors, the uncertainty of demand, maintaining the quality and quantity of the products at a reasonable level and on-time response to medical centers and finally yet importantly avoid waste caused by overproduction. To tackle these problems, we employed Markov decision process and simulation to ensure the accountability of the model. Eventually, the real managerial insight provided through gathering data regarding the number of casualties caused by road accidents in Semnan province, Iran, and the number of blood platelet ordered by the hospitals and coordination between medical centers and the Blood Transfusion Center. The results indicate the accessibility of the model by inventory manager and physicians in the transfusion center and the reduction of waste due to appropriate production planning.

A simple empirical model for blood platelet production and inventory management under uncertainty

This paper investigates a three-echelon supply chain problem in which multiple suppliers, a single manufacturer and a single retailer are participants. The manufacturer selects suppliers and estimates quantity of defective components purchased from the suppliers, but the quality information is unavailable for the manufacture due to asymmetric information. In addition, customers’ demands could not be predicated accurately either. Under this circumstance, quantity of defective components and demands of customers are all characterized as uncertain variables according to real trade. Based on uncertainty theory, three models under different criteria such as expected value criterion, chance-constrained one and measure-chance one are constructed for the problem and corresponding solution approach is proposed as well under uncertain environment. Finally, some numerical examples are given to show the applications of the problem.

Jiayu Shen

Papers

A three-echelon supply chain with asymmetric information under uncertainty