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Nowadays, product recovery and waste recycling are receiving more attention in order to reduce environmental pollution and production costs in the form of a closed-loop and sustainable supply chain. Also, designing a supply chain by considering resilience approaches can protect buyers against disruptions such as natural, human or technological disasters. On the other hand, efficient and effective financial supply chain management (FSCM) way is known as one of the main structures in line with the continuity and stability of the chain’s performance, and budget restrictions are of great importance considering the issue of scarcity of resources in the economy. This study has presented a multi-objective mixed integer linear programming (MOMILP) model of a single-period, multi-product and multi-level closed-loop supply chain, taking into account the dimensions of sustainability and resilience, emphasizing the balance between the initial budget and the cost of establishing facilities under uncertainty. subsequently, to eliminate the uncertainty of the demand parameters and costs, its robust counterpart was presented based on Pishvaee’s robust possibilistic programming (RPP) model. The augmented Epsilon Constraint method (AEC) and Non-dominated Sorting Genetic Algorithm (NSGA-II) were used to solve and evaluate it. [ABSTRACT FROM AUTHOR]

Nowadays, the lack of natural resources and reserves of raw materials, besides the increased production costs and the problems with burying and destroying industrial waste, have attracted attention to product recovery and waste recycling in the framework of a closed-loop and sustainable supply chain, also able to create a competitive advantage. On the other hand, researches indicate that taking resilience approaches into account in supply chain design may protect buyers against disruptions such as natural, human, or technological disasters. The present paper presents a multi-objective mathematical model of a single-period, multi-product, and multi-level closed-loop supply chain, considering the dimensions of resilience and sustainability under conditions of uncertainty. Hence, a deterministic mixed integer linear programming model is initially presented; subsequently, to eliminate the uncertainty of the demand parameters and costs, its stochastic counterpart was presented based on Pishvaee’s robust possibilistic programming (RPP) model. In order to solve the model, the Augmented Epsilon Constraint method was employed in the GAMS software environment. Ultimately, the model was solved and evaluated by a numerical example. [ABSTRACT FROM AUTHOR]

Twenty first century is described by knowledge development and its effect on all organizational dimensions. Today, knowledge is considered as the key and sometimes the only source of competitive advantage for organizations; that is why managers and organizations focus on utilizing some methods for knowledge acquisition, storage, and knowledge application in the present dynamic and competitive environment to provide access and quick transfer of knowledge in system using knowledge management. Therefore, the present research intends to present a model for identifying the effect of knowledge level on supply chain performance using modeling structural equations. Research statistical population included all automotive industries in Iran such as component makers, sale representatives, manufacturing units, etc. 350 were randomly selected as research sample and a questionnaire was distributed, 240 of which were returned. Finally, the positive, significant effect of business attitudes, organizational memory and individuals' knowledge on supply chain performance in Iran automotive industry was maintained; whereas, the positive, significant effect of customer knowledge, beneficiaries' relationships, knowledge in processes, and knowledge in manufacturing and services was rejected. [ABSTRACT FROM AUTHOR]