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This paper addresses a rollon–rolloff waste collection vehicle routing problem which involves large containers that collect huge amounts of waste from construction sites and shopping malls. In this problem, vehicles could only move one container at a time between customers’ locations, a depot, a disposal center, and a recycling center site. Other than a disposal center, a recycling center site is also added to the collection network based on which 10 trip types are defined. The problem aims to determine the optimal routes for minimizing the total distance traveled by vehicles resulting in a decrease in service time and cost. An initial solution is first generated by a heuristic algorithm and then, a hybrid meta-heuristic solution involving simulated annealing (SA) algorithm and hybrid SA and local search algorithm is proposed to tackle the problem. The data of the problem which is categorized into 12 classes are first generated randomly. Then, a straightforward solution representation is presented to encode the problem. The final generated results, the degree of their improvement and their computation time are compared with each other. Finally, conclusion remarks and future research directions are provided

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In this paper, the performance of [different] units of Water and Sewage Company in Isfahan Province was evaluated using Data Envelopment Analysis (DEA). The purpose of this study was to provide a clear picture of the relative performance of Decision-Making Units (DMUs) in 2018. The advantage of using the DEA model over parametric models is to measure the performance of units using specific weights. In this study, data were collected through desk studies, and then, analyzed using mathematical modeling (linear programming). MATLAB was used to analyze the data indicating that 11 out of 30 units were efficient and the rest were inefficient.

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Solid waste has become one of the most critical environmental issues in the world. Therefore, a waste management system to prevent further destruction of the environment is essential. Waste management includes collection, transport, cleaning, recycling, and disposal of the wastes. In recent years, due to environmental concerns, manufacturers have been forced to offer environmentally friendly products. So, the area of reverse logistics (RL) has recently received considerable attention, due to a combination of environmental, economic, and social factors.
In this research, the design of a multi-product and eleven-level reverse logistics network is conducted, which collects all the waste in one place and separates them according to the needs of the factories (in terms of the type and material of the waste, etc.) and sends them to the intended destination. This model can support all kinds of industries in which the revival of recycling and destruction of products.
This study provides a mixed integer mathematical model to reduce the costs of the whole system. The number of centers, the number of products and parts that should be sent from one center to another, the amount of CO₂ emissions, and the total cost of the model were determined. Finally, the sensitivity analysis was done on the parameters of the model. The model was validated by changing the input data in two different cases.
Sensitivity analyses are conducted on various parameters to illustrate the capabilities of the proposed model. The results reveal that the allowed cost of CO₂ emissions has a significant effect on the value of the objective function.

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DEMATEL is a multicriteria decision-making method used to analyse interrelationships and identify the cause‒and‒effect structure between different factors in a system. This method calculates the intensity of the factors’ influence on each other, divides them into two categories, "influencing" and "affected", and displays the relationships between them in the form of a directed graph. DEMATEL can help decision-makers identify key factors and set priorities for improving system performance or solving complex problems. Lean manufacturing is an approach to production management designed to eliminate waste in processes, reduce costs, and increase value for customers. DEMATEL is used in lean manufacturing to identify cause‒and‒effect relationships between factors affecting production. This method can identify key factors in eliminating waste, evaluate the impact of changes, and prioritize improvement actions. As a result, it helps optimize lean processes and achieves continuous improvement. In this study, 14 lean production tools were first identified by reviewing the literature. Then, 10 more comprehensive tools were selected on the basis of expert opinion. Finally, these 10 tools were prioritized via the fuzzy DEMATEL technique. The prioritization results show that effective tools, including the plan, do, check, act (PDCA) thinking method along with Kaizen, ABC analysis for inventory control, and visual inventory control at workstations, play a key role in improving lean production processes. On the other hand, effective tools, such as the use of failure mode and effects analysis to reduce equipment failure and the use of reliability based maintenance, have been more effective in optimizing production systems.