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On Location-Allocation Problems for Dimensional Facilities

JOURNAL OF OPTIMIZATION THEORY AND APPLICATIONS 2019年第2期182卷 730-767页

作者： Mallozzi, Lina Puerto, Justo Rodriguez-Madrena, Moises Univ Naples Federico II Naples Italy Univ Seville IMUS Seville Spain

This paper deals with a bilevel approach of the location-allocation problem with dimensional facilities. We present a general model that allows us to consider very general shapes of domains for the dimensional facilities, and we prove the existence of optimal solutions under mild assumptions. To achieve these results, we borrow tools from optimal transport mass theory that allow us to give explicit solution structure of the considered lower level problem. We also provide a discretization approach that can approximate, up to any degree of accuracy, the optimal solution of the original problem. This discrete approximation can be optimally solved via a mixed-integer linear program. To address very large instance sizes, we also provide a GRASP heuristic that performs rather well according to our experimental results. The paper also reports some experiments run on test data.

关键词： Bilevel optimization Dimensional facilities Optimal transport mass mixed-integer programming Heuristics

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Development of energy consumption optimization model for the electric vehicle routing problem with time windows

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JOURNAL OF CLEANER PRODUCTION 2019年 225卷 647-663页

作者： Xiao, Yiyong Zuo, Xiaorong Kaku, Ikou Zhou, Shenghan Pan, Xing Beihang Univ Sch Reliabil & Syst Engn Beijing 100191 Peoples R China China Aerosp Acad Syst Sci & Engn Beijing 100854 Peoples R China Tokyo City Univ Dept Environm Management Yokohama Kanagawa 2248551 Japan

Electric vehicles (EVs) are promising transportation tools for supporting green supply chain and cleaner production. In contrast to traditional fossil fuel-powered vehicles, which usually have a short range at lower speeds, EVs have a much longer (even double) range when traveling at lower speeds than high speeds. This feature has a major impact to the vehicle routing problem when EVs are used in the fleet. This study investigated the electric vehicle routing problem with time window (EVRPTW) considering the energy/electricity consumption rate (ECR) per unit of distance traveled by an EV as a function of the speed and load, referred to as EVRPTW-ECR for simplicity. As a consequence, the maximum range of an EV is estimated dynamically according to its speeds and loads along the route. A mixed-integer linear programming (MILP) model was developed for EVRPTW-ECR, where the EV's speed was treated as a continuous decision variable and the battery capacity, instead of a constant distance, was taken as the range restriction. Two linearization methods, i.e., the inner approximation and outer approximation, were introduced to handle the nonlinear relationship between the traveling speed and travel time with a given parameter epsilon to control the maximum permissible error. Computational experiments were carried out based on Solomon's instances to test the efficiency and effectiveness of the proposed model and methods, thereby demonstrating that the MILP model can be solved optimally for up to 25 customers by the CPLEX solver and partially optimized for large instances of up to 100 customers by using a heuristic approach. (C) 2019 Elsevier Ltd. All rights reserved.

关键词： Electric vehicle Green vehicle routing problem mixed-integer programming Continuous optimization

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Novel robust fuzzy programming for closed-loop supply chain network design under hybrid uncertainty

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JOURNAL OF INTELLIGENT & FUZZY SYSTEMS 2019年第5期37卷 6457-6470页

作者： Dehghan, Ehsan Amiri, Maghsoud Nikabadi, Mohsen Shafiei Jabbarzadeh, Armin Semnan Univ Fac Econ & Management Dept Ind Management Semnan Iran Allameh Tabatabai Univ Fac Management & Accounting Dept Ind Management Tehran Iran ETS Dept Syst Engn Montreal PQ Canada

In this paper, a mixed-integer nonlinear programming model is developed for a general edible oil closed loop supply chain network design problem under hybrid uncertainty which is then transformed to its linear counterpart. In order to cope with the hybrid uncertainty in input parameters, scenario-based and fuzzy- based parameters, a new approach is proposed including a novel robust fuzzy programming and an efficient method based on the Me measure. Furthermore, the performance of the proposed model is compared with that of other models. Finally, numerical studies and simulation are performed to verify our mathematical formulation and demonstrate the benefits of the proposed model.

关键词： mixed-integer programming edible oil supply chain closed loop supply chain Network design robust possibilistic programming stochastic programming

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Scheduling energy consumption for residential stand-alone photovoltaic systems

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SOLAR ENERGY 2019年 187卷 393-403页

作者： Cho, Dongjin Valenzuela, Jorge Auburn Univ Dept Ind & Syst Engn 1301 Shelby Ctr Auburn AL 36849 USA

Among various renewable energy sources, solar energy is considered an effective solution to the shortage of energy in the future. A stand-alone photovoltaic (PV) system can be particularly impactful in an isolated area where access to the grid is limited or unavailable. Because solar energy generation primarily depends on the availability of solar Irradiance over time, energy management is crucial, which in turn can also satisfy user comfort and system efficiency. In this paper, we propose an energy consumption scheduling model for a residential house with a stand-alone PV system and battery. We develop a mixed-integer optimization model that uses consumption patterns and appliance priority to schedule the use of appliances. We test our model under four scenarios based on region and season. The results demonstrate that the proposed model provides optimal schedules for operating the appliances. In addition, we conduct a sensitivity analysis on the PV array size and the battery capacity. We compare the optimized case with the non-optimized case.

关键词： Stand-alone PV system Optimal energy scheduling Battery Size mixed-integer programming

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Least-cost operation of a battery swapping station with random customer requests

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ENERGY 2019年 172卷 913-921页

作者： Mahoor, Mohsen Hosseini, Zohreh S. Khodaei, Amin Univ Denver Dept Elect & Comp Engn Denver CO 80210 USA

The Battery Swapping Station (BSS) is emerging as a viable means for fast energy refill of Electric Vehicles (EVs), in addition to many potential benefits in providing energy and ancillary services to the distribution grid. This paper focuses on developing a mathematical model for uncertainty-constrained BSS optimal operation that not only covers the random customer demands of fully charged batteries, but also leverages the available batteries to reduce its operation cost through demand shifting and energy sellback. The battery degradation is further modeled and formulated to ensure a practical solution. Numerical simulations on a test BSS demonstrate the effectiveness of the proposed model and show its viability in achieving the predefined objectives as discussed in this paper. (C) 2019 Elsevier Ltd. All rights reserved.

关键词： Battery swapping station (BSS) Electric vehicle (EV) Optimal scheduling mixed-integer programming Robust optimization Uncertainty

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Resilience-driven restoration model for interdependent infrastructure networks

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RELIABILITY ENGINEERING & SYSTEM SAFETY 2019年 185卷 12-23页

作者： Almoghathawi, Yasser Barker, Kash Albert, Laura A. Univ Oklahoma Sch Ind & Syst Engn Norman OK 73019 USA King Fahd Univ Petr & Minerals Syst Engn Dept Dhahran Saudi Arabia Univ Wisconsin Madison Ind & Syst Engn Dept Madison WI USA

Critical infrastructure networks such as electric power, water distribution, natural gas, transportation and telecommunications are the backbone of modern societies as they provide them with the services that are essential for their continuous functioning. However, these infrastructure networks are not isolated from each other but instead, most of them rely on one another to be functional. Hence, they are highly vulnerable to any disruptive event (e.g., components deteriorating, terrorist attacks, or natural disasters) which makes their restoration more challenging task for decision makers. In this paper, we study the restoration problem of a system of interdependent infrastructure networks following a disruption event considering different disruptions scenarios. We propose a resilience-driven multi-objective restoration model using mixed-integer programming that aims to maximize the resilience of the system of interdependent infrastructure networks while minimizing the total cost associated with the restoration process. The restoration model considers the availability of limited time and resources and provides a prioritized list of components, nodes or links, to be restored along with assigning and scheduling them to the available work crews. The proposed model is illustrated through a generated system of interdependent power-water networks, however it is applicable to any physically interdependent networks.

关键词： Interdependent networks Resilience Restoration Optimization mixed-integer programming

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Identification of the optimal agricultural structure and population size in a reservoir watershed based on the water ecological carrying capacity under uncertainty

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JOURNAL OF CLEANER PRODUCTION 2019年 234卷 340-352页

作者： Rong, Qiangqiang Cai, Yanpeng Su, Meirong Yue, Wencong Dang, Zhi Yang, Zhifeng Dongguan Univ Technol Ecoenvironm Sci Res Ctr Dongguan 523808 Peoples R China Guangdong Univ Technol Inst Environm & Ecol Engn Guangzhou 510006 Guangdong Peoples R China South China Univ Technol Sch Environm & Energy Guangzhou 510006 Guangdong Peoples R China

The optimal agricultural structure and population size within typical watersheds needs to be identified based on the water ecological carrying capacity (WECC). However, real-world systems of water ecological management are complicated as multiple uncertainties exist in the system parameters, which need some effective optimization methods to deal with. This research presents an inexact simulation-based fuzzy credibility-constrained mixed-integer programming (ISFCCMIP) model. Through integrating interval linear programming, fuzzy credibility-constrained programming, mixed-integer programming, global nutrient export from watersheds, and the Kirchner-Dillon model within a general framework, the developed ISFCCMIP model can effectively deal with the multiple uncertainties in the simulation and optimization processes of water ecological management systems. The developed ISFCCMIP model is applied to a real-world case study in the Xinfengjiang Reservoir Watershed. Results show that the total population that can be carried by the watershed WECC would decrease from [204885, 412367] to [121235, 271280], when the credibility level increases from 0.55 to 0.95. On the contrary, the total agricultural benefit would increase from [3.72, 5.06] x 10(8) to [3.75, 5.10] x 10(8) $. The total population in the base year far exceeds the watershed WECC. Although the total agricultural benefit in the base year is between the upper and lower bounds of the optimized results, the agricultural structure is not reasonable and needs to be adjusted. Concurrently, multiple results on the optimal agricultural structure and population size are obtained under different credibility levels and in different carrying capacity scenarios. Such results can provide a series of decision alternatives for watershed policy makers to consider the tradeoff between socio-economic development and water ecological protection. The results also assist the sustainable development of the Xinfengjiang Reservoir Watershed.

关键词： Inexact fuzzy programming mixed-integer programming Global nutrient export from watersheds Water ecological carrying capacity Agricultural structure

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Traffic Signal Optimization: Combining Static and Dynamic Models

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TRANSPORTATION SCIENCE 2019年第1期53卷 21-41页

作者： Koehler, Ekkehard Strehler, Martin Brandenburg Tech Univ Cottbus D-03046 Cottbus Germany

In this paper, we present a cyclically time-expanded network model for simultaneous optimization of traffic assignment and traffic signal parameters, in particular, offsets, split times, and phase orders. Since travel times are of great importance for developing realistic solutions for traffic assignment and traffic signal coordination in urban road networks, we perform an extensive analysis of the model. We give an example showing that a linear time-expanded model can reproduce realistic nonconvex travel times especially for use with traffic signals and we verify this by simulation. Furthermore, we show how exact mathematical programming techniques-namely, mixed-integer linear programming-can be used for optimizing the control of traffic signals. We provide computational results for real-world instances and demonstrate the capabilities of the cyclically time-expanded model by simulation results obtained with state-of-the-art traffic simulation tools.

关键词： traffic signal optimization traffic assignment cyclically time-expanded network flow over time link performance mixed-integer programming

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Optimal trajectories and normal load analysis of hypersonic glide vehicles via convex optimization

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AEROSPACE SCIENCE AND TECHNOLOGY 2019年 87卷 357-368页

作者： Wang, Zhenbo Univ Tennessee Mech Aerosp & Biomed Engn Dept Knoxville TN 37996 USA

Hypersonic trajectory optimization has been intensively investigated through different approaches;however, the normal-load-optimal entry problems were barely studied and reported in the literature. Finding the optimal trajectories with maximum or minimum peak normal load is essential to evaluate the maneuverability and structural strength of the vehicle. In this paper, both the maximum and minimum peak-normal-load entry trajectories are explored using convex optimization. Based on the previous work, the maximum-peak-normal-load entry problem is firstly addressed by a Big-M method and a line-search approach. Through successive relaxations, the nonconvex discrete-event optimal control problem associated with maximum-peak-normal-load entry is transformed into a sequence of mixed-integer convex optimization problems. Then, a line-search technique is introduced to improve the convergence of the proposed method. Additionally, a sequential convex programming method is designed to solve the minimum-peak-normal-load entry problem to comprehensively analyze the normal load during the entry flight. There are efficient solvers that can solve each relaxed convex subproblem with a global optimum if the feasible set of the subproblem is nonempty. The convergence and accuracy of the proposed methodologies are demonstrated by numerical simulations, and the feasibility of the converged solutions is discussed based on an entry-corridor approach. (C) 2019 Elsevier Masson SAS. All rights reserved.

关键词： Hypersonic vehicles Trajectory optimization Convex optimization mixed-integer programming Sequential convex programming

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Exact methods for order acceptance and scheduling on unrelated parallel machines

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COMPUTERS & OPERATIONS RESEARCH 2019年 104卷 159-173页

作者： Wang, Shijin Ye, Benyan Tongji Univ Sch Econ & Management Shanghai 200092 Peoples R China

This paper studies an order acceptance and scheduling (OAS) problem on unrelated parallel machines to maximize the total net revenue of accepted orders, which is the difference between sum of revenues and total weighted tardiness. Two mixed-integer programming (MIP) models are formulated, which are further improved with various enhancement techniques. A formulation-based branch-and-bound algorithm is developed in an attempt to handle complicated instances following the principle of "divide and conquer". Extensive computational experiments on various instances are conducted, and the results demonstrate the efficiency of the enhancement techniques for the formulations, as well as the effectiveness and efficiency of the formulation-based branch-and-bound algorithm. The proposed branch-and-bound algorithm can optimally solve instances with up to 50 jobs and different number of machines within the time limit of half an hour. (C) 2018 Elsevier Ltd. All rights reserved.

关键词： Order acceptance and scheduling Unrelated parallel machines mixed-integer programming Branch-and-bound

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