Logistics network is one of the most important parts of supply chains with significant shale in achieving sustainability across them. In this paper, we investigate a new multi-objective mixed integer linear programmin...
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Logistics network is one of the most important parts of supply chains with significant shale in achieving sustainability across them. In this paper, we investigate a new multi-objective mixed integer linear programming model for the design of multimodal logistics network. A bi-objective mathematical model is introduced and two conflicting objectives including the minimization of total cost and the total environmental impact are taken into account. effectiveenvironmental life cycle assessment-based method is incorporated in the model to estimate the relevant environmental impacts. Due to budget constraints, financing decisions for facility construction are considered in the proposed model. To cope with the model objective functions, theaugmentedepsilon-constraintmethod is applied. Computational analysis is also provided by using a cement multimodal rail-road logistics network case study to present the significance of the proposed model. Results show that utilizing the proposed multi-period optimization model influences the location of multimodal terminals and their construction time. Also, the results show that the use of the proposed model enhances theefficiency of terminals. On the other hand, computational results indicate that preferences of decision-makers and the importance of environmental objective have significant impacts on the topology of transportation network.
Machine scheduling problems are one of the basic manufacturing problems. Thus, there are a lot of study in the literature. In most of these studies, the problem is considered as single objective. Although the single o...
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Machine scheduling problems are one of the basic manufacturing problems. Thus, there are a lot of study in the literature. In most of these studies, the problem is considered as single objective. Although the single objective approach makes it easier to solve problems theoretically, it is often not possible to provide realistic solutions because almost all real-life problems have multi-objective properties. It is aimed to close this gap in the literature by using the multi-objective programming method that emerged as a powerful solution approach. The objectives are minimizing the makespan and minimizing the total tardiness. A matheuristic algorithm is developed for solving the considered problem. The performance of the algorithm is compared with the results of theaugmented e-constraint method. With the proposed matheuristic algorithm, both a solution time advantage is obtained and dominant solutions that could not be obtained with theaugmented e-constraint method are reached.
During theepidemic outbreak period, the number of infected people increased explosively. In order to effectively contain the further spread of theepidemic and treat infected people, it is necessary to make reasonabl...
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During theepidemic outbreak period, the number of infected people increased explosively. In order to effectively contain the further spread of theepidemic and treat infected people, it is necessary to make reasonable planning for the treatment of infected people and the distribution of materials. In this paper, a multi-objective mixed-integer programming model for the integrated design of emergency medical and material distribution networks is developed, in which the location of medical points, the allocation of infected people, and the distribution of medical materials are addressed in the multi-stage planning. Then, the multi objective model is solved by theaugmentedepsilon-constraintmethod. A realistic case study on Huangpu District of Shanghai in China is conducted to demonstrate the validity of the developed model. The results show that the integrated consideration of theemergency medical network and the material distribution network is more capable of reducing the total transportation distance and decreasing the total operating cost.
The municipal solid waste management (MSWM) system design considered here is effective in reducing supply chain costs and environmental risks. One of the practical approaches that governments use to encourage MSWM pra...
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The municipal solid waste management (MSWM) system design considered here is effective in reducing supply chain costs and environmental risks. One of the practical approaches that governments use to encourage MSWM practices is educating households with regard to reducing waste generation and increasing recycling and composting rates. This research aims to utilize a new multi-objective stochastic optimization model to design a MSWM system, taking public awareness and educating the public into consideration. Further, theefficiency induced by educating the public is also taken into account using its corresponding factors in the model. In this article, two types of truck for collecting the mixed and separated waste are appraised. Due to the unpredictability of some of the parameters of the MSWM models, allowances are made for uncertainty. The proposed model is applied to a real case in Tehran, Iran. To show the impact of educating households, the model is compared with a similar model that does not takeeducating the public into account. The results show a reduction of 40% in the total cost and an increment of 17% in the social impact as opposed to the model that does not takeeducating the public into consideration. This acknowledges that educating the public will improve the results obtained.
With the increasing demand of refined products and growing concern about carbon emissions, the planned multi-product pipelines, serving as the primary way of refined products transportation, should be designed reasona...
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With the increasing demand of refined products and growing concern about carbon emissions, the planned multi-product pipelines, serving as the primary way of refined products transportation, should be designed reasonably, economically, and low carbon-oriented so that the sustainable and environmentally friendly production and the rational construction of downstream oil supply chain can be achieved. Aiming at this issue, a multi-objective mixed-integer linear programming (MILP) model is proposed to minimize the total economic costs and CO2 emission simultaneously. Various actual process and technical constraints including pipeline construction, pump stations layout, pipeline hydraulic and pumps configurations are considered in the model. Based on theaugmented 8-constraintmethod, the conflicting objectives are dealt with and the Pareto front can be get. Finally, based on a predicted future scenario of regional refined products demand, the proposed model was successfully applied to a realword planned multi-product pipeline in China. Two cases are given to demonstrate the model's applicability and the influence of CO2 emission objective on the pipeline design scheme determination. Meanwhile, the trade-off between the two objectives was analyzed in detail. (C) 2019 elsevier Ltd. All rights reserved.
To successfully finalize projects and attain their determined purposes, it is indispensable to control all success criteria of a project. The time-cost trade-off (TCT) is known as a prevalent and efficient approach ap...
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To successfully finalize projects and attain their determined purposes, it is indispensable to control all success criteria of a project. The time-cost trade-off (TCT) is known as a prevalent and efficient approach applied when the planned finish date of a project is not admitted by stakeholders, and consequently, the project duration must be decreased. This paper proposes a new mathematical model under fuzzy uncertainty to deal with the project cost-risk-quality trade-off problem (CRQT) under timeconstraints. Because of the unique nature of projects and their uncertain circumstances, applying crisp values for some project parameters does not seem appropriate. Hence, this paper employs fuzzy sets to resolve these weaknesses. In this study, two approaches are presented to handle proposed fuzzy multi-objective mathematical model. First, fuzzy credibility theory and then goal attainment method are used. Secondly, the model is solved by a fuzzy method based on expected interval and value and augmented e-constraint method. A project from the literature review is adopted and solved by the presented methodology. The results demonstrate the accuracy and efficiency of the two proposed approaches for the introduced practical problem.
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