• Energy Research

Increasing energy demand and the fast depletion of fossil fuels have prompted the quest for sustainable energy sources. Biodiesel is a potential fossil fuel replacement that can be used in engines without modification. However, the commercial feasibility of biodiesel production is a major challenge. A resilient and cost-efficient biodiesel supply chain network is essential for commercialization. In addition, disruption risks arising from operational downtime, labor strikes, natural disasters, and uncertainty embedded in the data compromise the effectiveness of tactical and strategic level supply chain planning. In line with these requirements, an animal fat-based biodiesel supply chain model that reduces the total system cost and accounts for both disruption and operational risks is proposed. The proposed model determines the optimal production–distribution quantities and supports facility location and capacity decisions against multiple supply and demand interruption scenarios. A novel interactive solution technique, robust possibilistic flexible programming, which enables decision-makers to incorporate flexibility into model constraints, has been introduced. Furthermore, a p-measure constraint that ensures the lowest cost under disruption scenarios is used to control network reliability. A real-world case study is used to assess the suggested model and solution technique's applicability. The findings demonstrate a tradeoff between system reliability and nominal cost, showing that with a marginal increase in overall cost, the decisions can be secured against an uncertain environment. Biodiesel producers and distributors, as well as investors and regulators, may potentially benefit from the proposed model.

Increasing energy demand and the fast depletion of fossil fuels have prompted the quest for sustainable energy sources. Biodiesel is a potential fossil fuel replacement that can be used in engines without modification. However, the commercial feasibility of biodiesel production is a major challenge. A resilient and cost-efficient biodiesel supply chain network is essential for commercialization. In addition, disruption risks arising from operational downtime, labor strikes, natural disasters, and uncertainty embedded in the data compromise the effectiveness of tactical and strategic level supply chain planning. In line with these requirements, an animal fat-based biodiesel supply chain model that reduces the total system cost and accounts for both disruption and operational risks is proposed. The proposed model determines the optimal production–distribution quantities and supports facility location and capacity decisions against multiple supply and demand interruption scenarios. A novel interactive solution technique, robust possibilistic flexible programming, which enables decision-makers to incorporate flexibility into model constraints, has been introduced. Furthermore, a p-measure constraint that ensures the lowest cost under disruption scenarios is used to control network reliability. A real-world case study is used to assess the suggested model and solution technique's applicability. The findings demonstrate a tradeoff between system reliability and nominal cost, showing that with a marginal increase in overall cost, the decisions can be secured against an uncertain environment. Biodiesel producers and distributors, as well as investors and regulators, may potentially benefit from the proposed model.

Promotion of durable materials and products is a common approach to enhance sustainability. However, the effectiveness of such efforts lies on shifts in user behavior and consumption patterns, and these patterns are influenced not only by material aspects but also by social and experiential dimensions. It has been observed that the consumers’ consumption pattern, i.e., post-consumption behavior, is as harmful as production. However, this area remains largely unexplored. The primary purpose of this study is to explore sustainable garment design strategies to enhance emotional durability of garments and reduce pre-consumer and most importantly, the post-consumer waste. For this purpose, 18 garments were produced using ZWPC for pre-consumption waste reduction and DFD for post-consumption waste minimization. Three hypotheses were developed. Quantitative and qualitative data were collected through questionnaires and wear trials on the practicality of DFD implementation in garments. The results demonstrated that the combination of these strategies has the potential to curb both pre-consumer and post-consumer waste by designing garments that can enter the biological as well as technical cycle of circular fashion (CF). Furthermore, DFD is a success in increasing the use-life of a garment.

Promotion of durable materials and products is a common approach to enhance sustainability. However, the effectiveness of such efforts lies on shifts in user behavior and consumption patterns, and these patterns are influenced not only by material aspects but also by social and experiential dimensions. It has been observed that the consumers’ consumption pattern, i.e., post-consumption behavior, is as harmful as production. However, this area remains largely unexplored. The primary purpose of this study is to explore sustainable garment design strategies to enhance emotional durability of garments and reduce pre-consumer and most importantly, the post-consumer waste. For this purpose, 18 garments were produced using ZWPC for pre-consumption waste reduction and DFD for post-consumption waste minimization. Three hypotheses were developed. Quantitative and qualitative data were collected through questionnaires and wear trials on the practicality of DFD implementation in garments. The results demonstrated that the combination of these strategies has the potential to curb both pre-consumer and post-consumer waste by designing garments that can enter the biological as well as technical cycle of circular fashion (CF). Furthermore, DFD is a success in increasing the use-life of a garment.

Intricacy of the supply chains for deteriorating products, involving multiple retailers with unequal lot sizes and multiple deliveries is simplified in this article by optimizing the replenishment cycle, investment in preservation technology, and number of deliveries. This study proposes a multi-tier supply chain model consisting of a single manufacturer and multiple retailers. A single-setup multiple deliveries (SSMD) policy is adopted considering the synchronized cycle time of manufacturers with that of retailers and the delivery of unequal lot size for each retailer. Preservation technology is used at retailers to minimize the effects of deterioration in a way that the magnitude of decrease in deterioration reduces for additional investment in preservation technology. A centralized supply chain model is proposed by defining a nonlinear mathematical model for maximizing total profit through an analytical optimization technique and an algorithm. Numerical experiments are exhibited to validate the applications of the provided model. The results exhibit that the proposed preservation policy increases the product’s lifetime and the total profit by reducing the number of shipments/transportation and increasing the lot size. The SSMD policy helps to reduce the preservation cost and increase the total profit. Some managerial insights are provided for the decision makers for applying the proposed model.

Intricacy of the supply chains for deteriorating products, involving multiple retailers with unequal lot sizes and multiple deliveries is simplified in this article by optimizing the replenishment cycle, investment in preservation technology, and number of deliveries. This study proposes a multi-tier supply chain model consisting of a single manufacturer and multiple retailers. A single-setup multiple deliveries (SSMD) policy is adopted considering the synchronized cycle time of manufacturers with that of retailers and the delivery of unequal lot size for each retailer. Preservation technology is used at retailers to minimize the effects of deterioration in a way that the magnitude of decrease in deterioration reduces for additional investment in preservation technology. A centralized supply chain model is proposed by defining a nonlinear mathematical model for maximizing total profit through an analytical optimization technique and an algorithm. Numerical experiments are exhibited to validate the applications of the provided model. The results exhibit that the proposed preservation policy increases the product’s lifetime and the total profit by reducing the number of shipments/transportation and increasing the lot size. The SSMD policy helps to reduce the preservation cost and increase the total profit. Some managerial insights are provided for the decision makers for applying the proposed model.