The role of sustainability in supply chain is becoming critical due to increasing environment related problems and societal issues. Sustainable Supply Chain Management (SSCM) helps in reducing environmental degradation as well as social and economic implications. SSCM practices in Indian industries are in initial stage of implementation and industries find difficult to implement. Therefore, in present research, key enablers to initiate SSCM are recognized and analyzed. This research has recognized twelve enablers with the help of previous researches and expert survey. A Structural framework has been drawn with the use of Interpretive Structural Modeling (ISM) technique, to understand the relationship among the identified enablers and also to find the reliance of one on another. Further, MICMAC analysis has been employed for evaluating these identified enablers in accordance with Driving power and Dependence power. From ISM Methodology “Government policies and supportive systems” is found to be a key bottom enabler, which is important to implement the SSCM in Indian industries. For further future perspective, Decision Making Trial and Evaluation Laboratory (DEMATEL), can also be recommended for evaluation purpose. Present research may be helpful to find the importance of different enablers for successful implementation of SSCM in Indian industries.

The life of many people across the world can face various dangers with incurrence of incidents and unpredictable diseases. Incidents often require quick relief as they directly affect human lives. The process of planning, management and monitoring the flow of relief sources to injured and sick individuals is called relief logistics. When best relief services are provided through available sources, relief logistics appear. In this article, a multi-objective model for relief resources distribution facilities under an uncertain condition is investigated in two ways of demand satisfaction by considering the relief resources accessibility and demand satisfaction in a fuzzy logic. In the presented model, the concepts of cost, chance of demand satisfaction, elevation of response capability of system, discount levels for relief commodities, late satisfaction of demand, hub for accumulation of late and returned orders and special route for time significance in distribution of relief commodities are considered. For the first problem, the chance of relief resources accessibility and for the second problem, demands were investigated using fuzzy logic. Considering the conducted analysis, the demand amount is taken more in the second problem than the first one, which has led to an increase in the cost of the second problem. On one hand, the chance of demand satisfaction with no late orders is higher than the second problem. Satisfaction of demand occurs more in the second problem as well. Thus, these problems should be utilized in a way that suits the space of this problem. To solve the problem and to do the sensitivity analysis, we present a NSGA-II algorithm to deal with multi-objectiveness of the problem. A ε-Constraint method is also proposed to evaluate the performance of the proposed algorithm.

The player uses credit financing to perform profitable business. We analyze an economic order quantity model in which items have a fixed lifetime and deteriorate over time. The supplier offers the retailer a full credit period whenever the retailer orders more than or equal to a pre-specified quantity. If the retailer orders less than pre-specified order quantity, then the retailer will do partial payment to the supplier and avail of delay in payments for the remaining outstanding amount. The demand is price-sensitive. The retailer’s profit is maximized by setting appropriate retail price and replenishment time. The algorithm is developed to choose the best policy for the decision maker from the number of alternatives. Numerical data is used to validate the theoretical developments. Managerial insights are discussed. It is observed that for a given units to qualify for avail of partial credit period, increase in ordering cost decreases profit of the retailer. The increase in rate of the purchase cost to avail of delay payment suggests that to have a more profit, retailer should deplete stock before the allowable credit period.

Quantity discount is a usual term in business and has been a topic of interest for a long time, but have received very little attention. Many vendors offer different schemes to their customers to increase the existing size of order, which results in higher annual sale for the vendor and a lower purchasing price for the retailer. Therefore, the buyer adjusts his/her selling price, which influences the demand for the product. The objective of this paper is to develop an inventory model for deteriorating products with quantity discount and partial backlogging to determine the optimal ordering quantity for the retailer optimizing the total cost or profit of the associated model. A numerical example is also given to illustrate the model and its significant features.

There are many researches on project selection field, but few of them have considered environmental criteria in their studies. Moreover, there are many articles in evaluating risk but there is no article that considers value at risk concept to evaluate the amount of risk in multi project selection. We propose a multi objective mathematical model to address a situation in which several projects are candidate to be invested completely or partially. Three objective functions are considered in this paper. The first objective maximizes sum of the net present value of pure cash flow obtained from selected projects. In this objective, we consider the factor of time and its impact on value of money. In addition, we use the concept of value at risk (VAR) as the present value for the first time in project selection problems. Although green projects are more interesting, there are few articles, which address environmental issues. Hence, we consider the objective, which are related to environmental issues as the final criterion. Multi-Objective Differential Evolution algorithm (MODE) algorithm is applied to solve a problem, which is known as robust and efficient algorithm. Then computational results are compared with solutions obtained by NSGA-II algorithm which is well-known algorithm in this field with respect to seven comparison metrics.

Nowadays the use of fossil fuels as a non-renewable energy source has become a major challenge because of the pollution and the environmental impact. Substitution of biomass as an energy source and its supply chain design is the main question. Because of difficulties such as supply chain complexity, uncertainty in variables and selecting the site of bio-refineries many studies have been conducted in this regard. Studies in the field of biomass and biofuel production are described and classified. Also the strategic decisions such as choosing the sites, selecting energy conversation technology, ensuring economic, environmental, technical, and social sustainability and tactical decisions including allocating resources to productive plants, selecting transport modes, and types of warehouses are addressed in the reviewed papers. We have reviewed 140 papers in the interval between 1997 and 2016 and classified them based on the objective functions. The articles are classified based on their being single or multi objectivity, linearity or nonlinearity. Finally, a classification based on the regions in which the studies have been done.

In this paper we develop an inventory model for deteriorating items with price sensitive demand. Generally the vendor offers a cash discount or fix time period to the retailer to pay all the dues. According to the availability of money the retailer chooses his/her option. In this paper we discuss the possible cases of permissible delay and cash discount. The shortages are allowed in this model and are partially backlogged. Holding cost is considered as varying function of time, which reflects a more realistic concept. The purpose of this study is to optimize the overall cost of the system and to compute optimal ordering quantity. Numerical examples for different cases are also presented to illustrate the study. A sensitivity analysis with regard to distinct associated parameters is shown to make sure the constancy of the model.

This paper presents a survey to identify and rank the supply chain management factors influencing the quality of the products for small and medium enterprises (SMEs) in food industry. The study designs a questionnaire in Likert scale and distributes it among 238 randomly selected managers of SMEs in food industry in city of Tehran, Iran. Cronbach alpha is calculated as 0.851, which is well above the acceptable level. Using principle component with Varimax rotation, the study has determined four important factors including strategic management, product management, manufacturing process management, organizational resources, customer orientation, industry capacity, which influence the most on product quality improvement.

In this paper, an inventory model is studied with ramp type demand rate where holding cost is expressed as linearly increasing function of time. The study includes some features that are likely to be associated with certain types of inventory, like inventory of seasonal fruits and vegetables, newly launched fashion items, etc. When stock on hand is zero, the inventory manager offers a price discount to customers who are willing to backorder their demand. The optimum ordering policy and the optimum discount offered for each backorder are determined by minimizing the total cost in a replenishment interval.

Due to environmental issues, social concerns, increased pollution and enforced regulations; organizations are focusing to include green practices in their supply chain. This can be accomplished by adoption of green supply chain management (GSCM) practices. Therefore, GSCM is now a proactive approach for firms to increase their ecological performance, corporate image, achieve competitive advantages and sustainable business practices. This study identifies, evaluate and analyze the critical factors (CFs) for successful implementation of GSCM practices. The proposed study uses hybrid Fuzzy DEMATEL model to prioritize the identified critical success factors (CSFs) for GSCM adoption. Fuzzy approach is integrated with DEMATEL to deal with uncertainty arises in decision making process. To demonstrate the application of the proposed approach a case study from electronic industry is considered. This approach investigates the cause and effect relationships among the CFs for successful adoption of GSCM practices in Indian electronic organizations.