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Language: search.filters.language.EnglishSubject: search.filters.subject.Augmented epsilon constraint

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    Application of NSGA-II and Fuzzy TOPSIS to Time–Cost–Quality Trade-Off Resource Leveling for Scheduling an Agricultural Water Supply Project
    (Institute for Ionics, 2023-10-01)
    Access to sufficient and safe water particularly in vulnerable countries is one of the most important goals targeted by the United Nations for 2030. The agricultural water supply is crucial in arid areas such as Iran. In water supply projects, employers usually seek less duration and cost, and higher quality, however, contractors seek a reduction of fluctuations in project resources, especially human resources, and these goals may be in conflict with each other. Therefore, finding an optimal project schedule considering different project objectives is vital for managers to achieve stakeholders' satisfaction. In this study, the four main project objectives including time, cost, quality, and resource leveling as well as the activity dependencies and resource constraints are addressed through fuzzy optimization. The proposed model was first implemented on a small-sized project instance for validation; then, the model was solved by the Nondominated Sorting Genetic (NSGA-II) and Multi-objective Particle Swarm Optimization algorithms using the information of a real-world agricultural water supply project. The results of the first Pareto set for different alpha-cuts in relation to the fuzzy quality factor show a set of solutions and different alternatives for project implementation which leads to a number of execution modes each of which may result in achieving the project objectives. Finally, the most ideal solution with a duration of 178 days was selected using the fuzzy TOPSIS method. The findings demonstrate the validity of the proposed model concerning the needs of agricultural water supply organizations.
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    A sustainable hub location-allocation model considering the inspection of defective wagons in the rail freight network
    (Inderscience Publishers, 2025-01-01)
    The increasing demand for rail transport necessitates an effective transportation network design for the shipment of goods with minimum cost and time. Since the breakdown of wagons is a main delay factor in rail transportation, the maintenance and repairs of defective wagons becomes prominent. In this study, main stations are considered as hubs, and hubs are places where defective wagons are collected. For this purpose, a robust multi-objective mathematical model is proposed to minimise transportation costs considering customer demand. Also, the model seeks to minimise the total transportation time and emissions. The AEC method is exploited to solve and validate the proposed model. Moreover, the sensitivity analysis is performed to demonstrate the effect of changing the main parameters on the outcomes. The results show that repairs and maintenance can affect the capacity. Also, the findings demonstrate the applicability and validity of the proposed model in the railway sector. [Submitted: 29 May 2023; Accepted: 16 January 2024]
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