Bi-objective optimization for multi-modal transportation routing planning problem based on Pareto optimality

Sun, Yan; Lang, Maoxiang

doi:10.3926/jiem.1562

Cited by 31 publications

(56 citation statements)

References 16 publications

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“…The others rows are considered as restrictive conditions of the linear model, (formulas from 2 to 11). The liner model for the first criterion is as follow: x + x + x + x + x (2) 0.00 ≥ 0.50 0.50 2 1 x + x (3) x + x + x + x + x (6) 0.00 ≥ 0.50 0.50 2 1 x + x (7) 0.20 ≤ 0.20 0.20 0.20 0.20 0.20 (8) 0.50 ≤ 0.50 0.50 2 1 x + x (9) 0.50 ≤ 0.50 0.50 2 1 x + x (10) 0.50 ≤ 0.50 0.50 2 1 x + x (11) where x j -score of each alternative; j = 1,…,m -number of variants.…”

Section: Resultsmentioning

confidence: 99%

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Application of SIMUS method for assessment alternative transport policies for container carriage

Stoilova

2019

Engineering for Rural Development

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The purpose of this paper is to study the container transportation by rail and by road as alternative policies for carriage and to choose the effective one. A methodology to evaluate both transportation and ranking them has been developed. The Sequential Interactive Modelling for Urban Systems (SIMUS) as a tool to aid decision-making problems with multiple objectives has been applied. The methodology of the research includes two scenarios taking into account the weights of criteria -the first scenario does not use the weights of criteria and for the second one it is necessary to apply the weights which are pre-defined. The methodology of the research includes four steps. The first step defines the quantitative and qualitative criteria for assessment of container transportation. The investigated strategies for transportation that have been studied are intermodal rail transport and road transport. The weighs of criteria have been determined in the second step. They are used only in the second scenario. The third step of the research formulates the alternatives of carriage by containers and includes two ways of transportation: by container block trains and by trucks. The SIMUS method has been applied in the fourth step for ranking the variants of transportation. The method solves successive scenarios formulated as linear programming. This step involves ranking of alternatives and the choice of optimal type of transportation. The methodology is approbated for the routes Sofia-Varna from the railway and road network of Bulgaria. It was found that the technologies that include rail transport are the best variants of transportation. The methodology can be applied for assessment different types of transportation and different transport policies.

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Section: Resultsmentioning

confidence: 99%

“…18.N284 into account carbon emissions and intermodal transfers. The problem of multi-modal transportation routing planning is investigated in [8]. A model based on bi-objective mixed integer linear programming with objective minimization of the total transportation cost and the total transportation time has been elaborated.…”

Section: Introductionmentioning

confidence: 99%

Application of SIMUS method for assessment alternative transport policies for container carriage

Stoilova

2019

Engineering for Rural Development

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“…First, for large sized stochastic mixed integer programming, some advanced solution methods, i.e., meta-heuristic [51,52], should be developed and applied to the design of a reverse logistics system for WEEE in order to improve the computational efficiency and effectiveness. Second, the model may be further developed into a multi-objective programming model in order to take into account more comprehensive considerations in the design of the reverse logistics system for WEEE, i.e., risk [53][54][55][56][57], saving of resources [42], etc. Third, the model is developed primarily for addressing the general characteristics of the reverse logistics system for WEEE from a strategic perspective; however, some specific technologies are used in the sorting and recycling processes of WEEE, so future research may focus on the economic efficiency and environmental impacts of those specific technologies for the processing and treatment of WEEE.…”

Section: Discussionmentioning

confidence: 99%

A Stochastic Programming Approach with Improved Multi-Criteria Scenario-Based Solution Method for Sustainable Reverse Logistics Design of Waste Electrical and Electronic Equipment (WEEE)

Solvang

2016

Sustainability

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Today, the increased public concern about sustainable development and more stringent environmental regulations have become important driving forces for value recovery from end-of-life and end-of use products through reverse logistics. Waste electrical and electronic equipment (WEEE) contains both valuable components that need to be recycled and hazardous substances that have to be properly treated or disposed of, so the design of a reverse logistics system for sustainable treatment of WEEE is of paramount importance. This paper presents a stochastic mixed integer programming model for designing and planning a generic multi-source, multi-echelon, capacitated, and sustainable reverse logistics network for WEEE management under uncertainty. The model takes into account both economic efficiency and environmental impacts in decision-making, and the environmental impacts are evaluated in terms of carbon emissions. A multi-criteria two-stage scenario-based solution method is employed and further developed in this study for generating the optimal solution for the stochastic optimization problem. The proposed model and solution method are validated through a numerical experiment and sensitivity analyses presented later in this paper, and an analysis of the results is also given to provide a deep managerial insight into the application of the proposed stochastic optimization model.

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“…We consider a general triangular fuzzy number r a "`a L , a M , a U˘w here a L >a M >a U >0, let µ r a pxq denote its membership function whose expression is as Equation (20).…”

Section: Crisp Equivalent Of the Fuzzy Chance Constraint Setsmentioning

confidence: 99%

On Solving the Fuzzy Customer Information Problem in Multicommodity Multimodal Routing with Schedule-Based Services

Sun

Lang

2016

Information

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Abstract:In this study, we combine the fuzzy customer information problem with the multicommodity multimodal routing with schedule-based services which was explored in our previous study [1]. The fuzzy characteristics of the customer information are embodied in the demanded volumes of the multiple commodities and the time windows of their due dates. When the schedule-based services are considered in the routing, schedule constraints emerge because the operations of block container trains should follow their predetermined schedules. This will restrict the routes selection from space-time feasibility. To solve this combinatorial optimization problem, we first build a fuzzy chance-constrained nonlinear programming model based on fuzzy possibility theory. We then use a crisp equivalent method and a linearization method to transform the proposed model into the classical linear programming model that can be effectively solved by the standard mathematical programming software. Finally, a numerical case is presented to demonstrate the feasibility of the proposed method. The sensitivity of the best solution with respect to the values of the confidence levels is also examined.

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Bi-objective optimization for multi-modal transportation routing planning problem based on Pareto optimality

Cited by 31 publications

References 16 publications

Application of SIMUS method for assessment alternative transport policies for container carriage

Application of SIMUS method for assessment alternative transport policies for container carriage

A Stochastic Programming Approach with Improved Multi-Criteria Scenario-Based Solution Method for Sustainable Reverse Logistics Design of Waste Electrical and Electronic Equipment (WEEE)

On Solving the Fuzzy Customer Information Problem in Multicommodity Multimodal Routing with Schedule-Based Services

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