Supplier selection, order allocation and production planning are important and challenging decisions in supply chain management. There are many studies on mentioned topics separately. In this paper, a multi-objective mathematical model is proposed to optimize a sustainable supplier selection problem with order allocation and production planning simultaneously. This study considers a multi-supplier, multi-product, multi-item and multi-period supply chain. The designed mathematical model seeks to maximize total profit and minimize unsatisfied demand and total risk along with enforcing sustainability criteria in selecting suppliers. Supplier selection is a virtual process in every manufacturing company. On the other hand, this research considers all the important aspects of this problem. Therefore, the proposed framework can be implemented in many different companies like electronic, food, chemical industry. The proposed model is solved utilizing two metaheuristic algorithms including NSGA II and MOPSO. Moreover, algorithms are tuned utilizing Taguchi analysis. Furthermore, ten sample problems are generated and results are compared to identify the best algorithm for the proposed model.

The strong competition in today's global markets and huge customer attention to factors such as price, quality, time delivery and product variety has caused the investors to focus on supply chain management. In this regard, selecting the choosing and determining the quota of each one is one of the most important and crucial decisions that not only is responsible for supplying the parts, but also accountable for maintaining the organization in the competitive environment. This paper is devoted to determine the optimal order of each product in a multi-objective and multi-period problem. The considered multiple objective functions include minimizing total purchase and order costs, transportation costs, percentage of returned and delayed products, also maximizing the total reliability of selected suppliers according to the necessary of supplying for each product. Due to the existence of unsustainable situation in the real world, in this paper the sustainable approach is introduced to create robust result.

Supplier Selection plays an important role in supply chain management. Attention to sustainability in supply chain makes supplier selection more controversial. Current studies have concentrated on economic factors for selection and evaluation of suppliers and there are few emphasis on triple factors including economic, environmental and social elements as the sustainability factors. Also, the methods that are used for supplier evaluation is almost based on linear programming, multi-objective programming, goal programming, integer programming, and the other exact methods. But in real situation, the evaluation criteria are ambiguous, qualitative and verbal. So, in this study, a new technique based on Grey theory is proposed for supplier evaluation that can be used in ambiguous situations. This technique helps managers to decide on supplier selection problems in real scenarios. In this study, the economic, environmental and social indices for suppliers' evaluation are identified based on experts' opinion and by applying Grey theory a technique is developed for suppliers' evaluation. The novelty of this research is to develop a new technique with more levels of analysis in ambiguity, considering sustainability factors. The case study of this research is steel industry.

Nowadays supply chain sustainability efforts are continuing to grow globally.  While the focus of typical supply chain management mostly is on the speed, cost and reliability of operations, sustainable supply chain management adds the goals of upholding environmental, financial and social responsibilities. Although the worth of supply chain management in large-scale projects, in particular, the construction industry has been recognized currently, its execution remains subject to significant challenges. One of the main challenges is the complexity of the sustainable suppliers’ selection. They can enhance the profitability and success of the project-oriented construction organizations. In this respect, this article aims to apply fuzzy Utilities-Additives STAR (UTASTAR), the extended Utilities Additives Method for multiple criteria decision, to select sustainable suppliers and evaluate general utility function of the problem. Finally, since this method belongs to compensatory multi-criteria decision-making models the results obtained through the application of the fuzzy UTASTAR were compared with some selected models from the compensatory subgroup. According to comparative results, fuzzy UTASTAR can identify deviation from actual utility of alternatives using upper and lower estimations. As a result, this study shows that the rankings produced by the fuzzy UTASTAR method are more trustworthy for selecting suppliers in ensuring the sustainable development.

In recent years, supplier selection (SS) has been one of the fundamental issues in the supply chain(SC). Sustainable suppliers are selected based on the quantitative and qualitative evaluation of economic,environmental, and social studies. This paper examines sustainable SS and order allocation (OA) for a singleproduct in a multistage setting. To model the problem, in the first step, the best-worst method (BWM) is usedto determine the weights of the sustainability criteria. Then, given the uncertainty of personal judgment,evidential reasoning (ER) is used to evaluate suppliers. Suppliers are also compared based on the minimumand maximum utility function in case of lack of information. In the next step, a model is designed to optimizesuppliers' total purchase value (TVP) and optimize total purchase cost (TCP). Demand is assumed to berandom. This assumption leads to a set of scenarios based on the time horizon. To solve the model, a dynamicprogramming (DP) is presented. Finally, a case study is given to detail the methodology.

Background and Objective: Reducing environmental pollution and selecting sustainable suppliers can lead to improving the stability situation and reducing the risk of supply chain disruption. The purpose of this study was to design a model for selecting stable resilient suppliers in the supply chain of Shahid Ghandi Company with intuitive fuzzy AHP approach. Material and Methodology: The present research is an applied-developmental goal in terms of collecting descriptive information and in terms of the nature of data. The present study consists of two main parts. In the first part, using research literature, the criteria for selecting a stable resilient supplier were identified. To obtain the indicators, after reviewing the theoretical literature of the research, 76 indicators were identified for evaluation of sustainable supplier and 50 indicators for evaluation of resilient supplier, which after four stages of supply chain experts in Shahid Ghandi factories using Delphi model method Finally, 15 suitable indicators for sustainability and 15 suitable indicators for resilience were identified, then a questionnaire was distributed among the employees in the supply chain of Shahid Ghandi Company and based on 136 questionnaires, the model of selecting a resilient sustainable supplier Confirmatory factor analysis method was approved and then intuitive fuzzy AHP method was used to select the supplier. Findings: Sustainability indices were classified into three sections: economic, social and environmental, as well as resilience indices in three sections: absorption capacity, adaptive capacity and restorative capacity. It was spread among experts. Discussion and Conclusion: The results showed that priority is given to economic indicators, absorption capacity, remedial capacity, adaptive capacity, social and environmental, respectively, and finally suppliers were prioritized. Also, among the sub-indicators, cost and quality are the most important They were.

Supplier selection has been considered as one of the important decisions taken by firms in supply chain management to enhance profitability in this competitive era. With the emergence of environmental policies and social concerns, companies are forced to consider triple bottom line including economic, environmental, and social attributes into their supply chain activities. Since different criteria affecting sustainable supplier selection conflict with each other, sustsainable supplier selection problem is considered as a multi-criteria decision-making problem. Furthermore, the evaluation of numerous conflicting requirements suffers imprecise and vague in decision makers’,judgments. In this paper, an efficient Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method which is integrated by gray theory is developed to deal with uncertainty and imprecise among decision makers’,judgments in the most right sustainable supplier selection. The proposed method was performed on tool industry as case study to select the most sustainable alloy supplier which involves three main criteria and twelve sub-criteria. The results indicated that Ara Sanat Asia company performs better than the other companies due to high contribution in the environmental and social criteria in addition to economic criteria as traditional metrics.

Sustainable supplier selection in the long term, lead to a competitive advantage in the supply chain. This study aims to present a conceptual model for sustainable supplier selection in the SAIPA supply chain. In first, based on a comprehensive literature review 58 indicators identified to assess the sustainable suppliers. After checking the indicators by automotive industry's supply chain experts, only 17 indicators were verified. Then, the questionnaire distributed among experts in the SAIPA's supply chain, and finally 191 questionnaires was obtained. In next sustainable supplier selection model was estimated by using confirmatory factor analysis and the indicators explained three latent variables (economic, social and environmental). The results achieved by this research model revealed that the sustainable suppliers in order of priority to the aspects of "social", "economic" and "environmental" conditions. The results achieved by this research model revealed that the sustainable suppliers selection explained by "social", "economic" and "environmental" latent variables. Also the priorities of each sub-index was determined in explained “sustainable suppliers selection” model.