A robust green fuzzy multi-objective model to location - allocation - routing – inventory problem in optimizing the urban waste management process using meta-heuristic algorithms

This study presents a new form of the problem of location, allocation, routing and inventory in the municipal waste management system by considering three economic, social and environmental issues. In the economic sector, various types of costs related to collection Municipal waste is examined in such a way that at the same time the total system costs and the number of machines required for waste collection in the whole network are minimized. Also in the social and environmental sector, it seeks to provide a model for finding the shortest path between waste collection tanks in the city to the final collection and recycling site. The research problem is formulated in the form of a multi-objective nonlinear programming model of complex integer. Also, to control the degree of uncertainty of some parameters in the research model, the fuzzy robust method has been used. Since the problem of this research is np-hard type and also the optimal amount of variables in these problems interact with each other, the multi-objective colonial competition algorithm and multi-objective genetic algorithm have been used for the final solution. The results of solving different scenarios as well as validating the results of the proposed algorithms show that the average error of the multi-objective metaphorical competition algorithm is lower than the multi-objective genetic algorithm in solving different scenarios, which indicates the high efficiency of the algorithm for a wide range of problems. It comes in different sizes.