Mohammad Nikzamir; vahid baradaran; Yunes Panahi
Abstract
Health care solid wastes include all types of waste that are produced as a result ofmedical and therapeutic activities in hospitals and health centers. About 15% to20% of these waste materials are infectious waste, which falls within the categoryof hazardous materials. Infectious waste is the one that ...
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Health care solid wastes include all types of waste that are produced as a result ofmedical and therapeutic activities in hospitals and health centers. About 15% to20% of these waste materials are infectious waste, which falls within the categoryof hazardous materials. Infectious waste is the one that must be treated beforedisposal or recycling. Hence, this paper seeks to develop a bi-objective mixedinteger programming model for the infectious waste management. In the proposedmodel, in addition to minimizing the chain costs, the reduction of risks for thepopulation exposed to the spread of contamination resulting from infectious wasteis also considered. For this purpose, a multi-echelon chain is proposed by takinginto account the green location-routing problem, which involves the location ofrecycling, disposal, and treatment centers through various treatment technologiesand routing of vehicles between treatment levels and the hospital. The routingproblem has been considered to be multi-depot wherein the criterion of reducingthe cost of fuel consumption of heterogeneous cars is used for green routing.Finally, a hybrid meta-heuristic algorithm based on ICA and GA is developedand, following its validation, its function in solving large-scale problems has beeninvestigated. Results show that the proposed algorithm is effective and efficient.
Vahid Baradaran; Armaghan Azarikhah
Abstract
The development of a variety of public transportation systems that cover different areas, has made it difficult for passengers and users to choose the type of transportation system and appropriate route between two specified departures. In large cities such as Tehran, a network of public transportation ...
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The development of a variety of public transportation systems that cover different areas, has made it difficult for passengers and users to choose the type of transportation system and appropriate route between two specified departures. In large cities such as Tehran, a network of public transportation systems, called multi-modal systems, are consist of stations as nodes and public transport vehicles intermediate between the two consecutive stations as arcs. Travelers are looking continuously for a way to find the optimal route in complex multi-modal transportation networks to reach their desired destination with minimal cost and confusion. In this paper, a multi-objective programming model with three objective functions has been developed for routing in multi-modal transport systems. The objectives of the proposed model are to minimize the cost, travel time and the number of vehicle types. By examining the validation of models by test issues, two exact and meta-heuristic algorithms (ant colony algorithm) have been developed to solve the proposed model. The results show that problem solving by exact method for networks with more than 15 nodes are non-operating, while the meta-heuristic algorithm provides the same problems with same precision in the exact method but with logical time.
Zahra Safari
Abstract
By increasing attention to environmental issues, the problem of design closed-loop supply chain has been more important. The integrated design of closed-loop supply chains as one of the most important issues in the management of supply chains involve determining the location and number of required facilities ...
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By increasing attention to environmental issues, the problem of design closed-loop supply chain has been more important. The integrated design of closed-loop supply chains as one of the most important issues in the management of supply chains involve determining the location and number of required facilities (production, collection, recycling and disposal) in the forward and reverse supply chain, inventories in every facility and flows between them. In this paper, a closed-loop supply chain with diverse products (multi-product) has been studied and a linear bi-objective mathematical model is proposed to reduce the total costs and the emissions in the network with determining the strategic and operational variables. Because of the uncertainty in parameters of proposed model such as customer demands or returns, the proposed model under uncertainty (robust optimization) is developed. The closed-loop supply chain of glass bottles is studied and modeled to minimize the total costs and production of carbon dioxide by proposed model. Finally, a sensitivity analysis of robust optimization model was conducted.
