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Management of waste is one of the major challenges faced by many developing countries. This study therefore attempts to develop a circular economy (CE) model to manage wastes and closing the loop and reducing the generation of residual wastes in Indian municipalities. Through extant literature review, the researchers found 30 success factors of CE implementation. Using the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) SIMOS approach, the rating and weight of decision makers (DMs) for each factor were collected. A structured questionnaire has been developed incorporating all these 30 factors, to extract the most important factors. The data was collected from top 10 officials (DMs) from the Chennai municipality, who handle three regions (metropolitan, suburbia and industrial). Based on the TOPSIS SIMOS analysis, nine CE implementing factors (critical success factors (CSFs)) among the 30 variables that were significant based on the cut-off value was identified. A CE model has been proposed based on these nine CSFs for waste management in India.

This paper addresses a distribution problem in a multi-product, multi-echelon supply chain. We develop a mixed integer linear programming formulation that considers allocation of vehicles with varying capacities for the transportation of products between the stages of the supply chain. The cost of transportation includes the fixed and variable costs of using the vehicles. The proposed formulations are solved optimally up to certain sizes, and we propose a heuristic based on total opportunity penalty cost method to solve the large sized problems. These proposed solution procedure is tested over a set of hypothetical problem sets. The results indicate that the proposed heuristic algorithm yields solutions within 5% from the optimal solutions.

This paper addresses a distribution problem in a multi-product, multi-echelon supply chain. We develop a mixed integer linear programming formulation that considers allocation of vehicles with varying capacities for the transportation of products between the stages of the supply chain. The cost of transportation includes the fixed and variable costs of using the vehicles. The proposed formulations are solved optimally up to certain sizes, and we propose a heuristic based on total opportunity penalty cost method to solve the large sized problems. These proposed solution procedure is tested over a set of hypothetical problem sets. The results indicate that the proposed heuristic algorithm yields solutions within 5% from the optimal solutions.