Nowadays, the study of disasters such as earthquakes and their consequences, specifically in metropolises such as Tehran, has attracted significant attention. Allocating relief goods to distribution centres before the earthquake and providing relief services to the injured can reduce the fatality rate. Therefore, it seems quite necessary to present a certain routing and allocation scheduling model of relief vehicles to serve the injured. In this research, a mathematical model was proposed to minimise the unmet demands and transportation costs of relief vehicles and in the affected areas. Regarding the inherent uncertainties of disasters, we developed a robust scenario-based optimisation model for relief logistics networks to reduce the risk of fatality and provide near-optimal solutions for different possible disaster scenarios. We showed that the proposed cooperation plan produces a situation with additive supper property, which means that this type of cooperation will finally lead to a greater incentive for aid agencies to form larger coalitions. Furthermore, we proposed a set of cooperative game theory methods to distribute the cost-saving of the cooperation fairly.

In the cellular industry, the components of products are increasingly being manufactured by multiple companies, which are distributed across different regions resulting in increased production costs. Here, a cooperative cellular manufacturing system is introduced to decrease these costs. A mathematical programming model has been proposed, which evaluates the production cost when companies work independently and the model is then extended to consider coalitional conditions in which the companies cooperate as an integrated cell formation system. A key question that arises in this scenario is how to arrange the cells and machines of multiple companies when their cell formation systems are designed cooperatively. Through a realistic case study of three high-tech suppliers of the Mega Motor Company, we show that these companies can reduce the costs through a cooperative cellular manufacturing system. We then compute the cost saving of each coalition of companies obtained from cooperation to get a fair allocation of the cost savings among the cooperating firms. Four cooperative game theory methods including Shapley value, τ -value, core-center, and least core are proposed to examine fair sharing of cost saving. A comprehensive analysis of the case study reveals important managerial insights.

Purpose: Waste production and related environmental problems have caused urban services management many problems in collecting, transporting and disposal of waste. Since collecting and transporting waste are important parts of waste management budget, it is necessary to apply an appropriate method to reduce costs of collection. The aim of this study is to design a new model for urban waste collection vehicle routing problem with time windows and energy generating from waste.Design/methodology/approach: A multiobjective model is presented with the objectives of minimizing cost of waste collection, reducing emissions from environmental pollutants and increasing income of recycles trade and energy recovery. Concerning the complexity of the model and its inability to solve large-scale problems, hyperactive genetic algorithms and multiple objective particle swarm optimization are applied.Findings: The proposed model not only affects costs and income but also reduces the emissions of environmental pollutants. To solve the formulated model, multitarget approaches are applied on the processing site of Kermanshah city as a case study. The solutions of these algorithms and the exact method of partial constraints are compared and the outcomes are verified by numerical analysis by solving various examples in small, medium and large scales. The proposed model helps to collect urban wastes in the shortest possible time in addition to reducing the total cost, revenues from the sale of recycled materials and energy generation.Research limitations/implications: Waste collection is related to VRP issue. Considering the environmental requirements in waste management, the concept of green supply chain is approached. This study provides a better understanding of urban waste management by examining various articles and combining economic and environmental dimensions. Waste management with a green approach and energy production from disposable waste involves many common stakeholders.Practical implications: This study suggests that proper waste management can generate revenue from municipal waste. Moreover, it reduces cost of collecting and emission of environmental pollutants. These findings could motivate companies to waste management with a sustainable approach.Originality/value: The proposed model boosts the current understanding of the waste management and energy generation of waste. The paper adds additional values by unveiling some key future research directions. This guidance may demonstrate possible existing and unexplored gaps so that researchers can direct future research to develop new processes.