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Binary programs for asymmetric betweenness problems and relations to the quadratic linear ordering problem

EURO JOURNAL ON COMPUTATIONAL OPTIMIZATION 2023年第1期11卷

作者： Mallach, Sven Univ Bonn High Performance Comp & Analyt Lab Friedrich Hirzebruch Allee 8 D-53115 Bonn Germany

We present and compare novel binary programs for linear ordering problems that involve the notion of asymmetric betweenness and expose relations to the quadratic linear ordering problem and its linearization. While two of the binary programs prove particularly superior from a computational point of view when many or all betweenness relations shall be modeled, the others arise as natural formulations that resemble important theoretical correspondences and provide a compact alternative for sparse problem instances. A reasoning for the strengths and weaknesses of the different formulations is derived by means of polyhedral considerations with respect to their continuous relaxations.& COPY;2023 The Author(s). Published by Elsevier Ltd on behalf of Association of European Operational Research Societies (EURO). This is an open access article under the CC BY license (http://creativecommons .org /licenses /by /4 .0/).

关键词： Linear ordering problem Betweenness problem Facility layout problem mixed-integer programming Binary quadratic programming

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Maximization of Traffic Flow through Intersection by Branch-and-Bound Method

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IFAC Proceedings Volumes 1983年第4期16卷 149-155页

作者： S. Guberinić S. Reljić G. Senborn Mihailo Pupin Institute Belgrade Yugoslavia

This paper deals with the problem of optimal control at an isolated oversaturated intersection equipped with a signa1-group-oriented controller. The problem we consider is to determine elements of the signal plan (stages, their duration and sequence) so as to maximize the number of vehicles that can pass through the intersection during one cycle. The concents of signal plan structure, admissible stage sequences, and structural constraints are introduced, and the optimization problem is stated as the problem of finding the best closed path through the graph of possible sequences. The optimization technique is of branch-and -bound type. The proposed method gives an exact procedure for simultaneous determination of all signal plan elements, except for the cycle time. An illustrative example is also included.

关键词： Traffic control optimization combinatorial mixed-integer programming branch-and-bound method

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On the feasibility of using canals for waste collection in Amsterdam

Transactions in Urban Data, Science, and Technology

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Transactions in Urban Data, Science, and Technology 2022年第1-2期1卷 86 - 102页

作者： Snoweria Zhang Fábio Duarte Xuezhen Guo Lenna Johnsen Ruben van de Ketterij Carlo Ratti Senseable City Lab Massachusetts Institute of Technology Cambridge MA USA Operations Research and Logistics Group Wageningen University and Research Centre Netherlands

Amsterdam, a growing city of over 800,000 people in the Netherlands, is struggling to collect waste. While residents in most districts of the city use underground bins to deposit their garbage, the historic Centrum district continues to rely on curbside collection. As such, the streets around the UNESCO-World-Heritage canals are lined with garbage bags as trash trucks rumble down roads centuries old and ill-fitted for vehicles of such size. This paper assesses the viability of moving Centrum trash collection to the canals with a fleet of tug boats and floating dumpsters. It does so by using a combination of GIS tools and integer programming to determine the quantity and optimal collection locations while ensuring that an average Centrum resident walks no farther than denizens of the other Amsterdam districts. Additionally, it proposes a schedule for emptying floating dumpsters based on one comparable to the current truck system. The results of this paper suggest that mobile trash collection using the canals is a viable solution that could reduce noise, pollution, and congestion, thus improving the quality of Amsterdam’s historic cityscape.

关键词： Waste-collection boats autonomy GIS mixed-integer programming

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A dual-level stochastic fleet size and mix problem for offshore wind farm maintenance operations

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INFOR: Information Systems and Operational Research 2021年第2期59卷 257-289页

作者： Magnus Stålhane Kamilla Hamre Bolstad Manu Joshi Lars Magnus Hvattum a Department of Industrial Economics and Technology Management Norwegian University of Science and Technology Trondheim Norway b Faculty of Logistics Molde University College Molde Norway

This paper studies the strategic problem of finding a cost optimal fleet of vessels to support maintenance operations at offshore wind farms. A dual-level stochastic model is formulated, taking into account both long-term strategic uncertainty and short-term operational uncertainty in a single optimization model. The model supports wind farm owners in making strategic decisions regarding the number, placement, charter length, and types of vessels to charter, to meet maintenance demands throughout the lifetime of a wind farm. To evaluate the quality of strategic fleet size and mix decisions, the model also considers the operational decisions of how to utilize the fleet to support maintenance operations. The model accounts for strategic uncertainties that have not been considered in previously developed optimization models for offshore wind, such as uncertainty related to long-term trends in electricity prices and subsidy levels, the stepwise development of wind farms, and technology development in the vessel industry. To solve the proposed stochastic programming model we have developed an ad hoc integer L-shaped method, with customized optimality cuts. The computational experiments show that the proposed method outperforms solving the deterministic equivalent using a commercial MIP solver.

关键词： Stochastic programming hierarchical planning multilevel planning mixed-integer programming integer L-shaped method multi-horizon

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Synthesis of carbon capture, utilization, and sequestration processing pathways using state-task network representation

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IFAC-PapersOnLine 2023年第2期56卷 6888-6893页

作者： Wonsuk Chung Ali S. Al-Hunaidy Hasan Imran Jay H. Lee Clean Energy Research Center Korea Institute of Science and Technology (KIST) 02792 Seoul Republic of Korea Carbon Management Division Research & Development Center Saudi Aramco Dhahran 31311 Saudi Arabia Mork Family Department of Chemical Engineering and Material Science University of Southern California VHE310 3651 Watt Way Los Angeles California United States

Synthesis of sustainable processing pathway is an important initial step in deciding investments in carbon capture, utilization, and sequestration (CCUS). For a best decision, it is necessary to analyze a very large number of potential processing pathways at once in terms of their economics and net carbon emission. Such analysis may also reveal which parts of a pathway incur significant portions of the costs and carbon emissions, suggesting hotspots for improvement. Frameworks used should also be flexible enough to accommodate varying feed conditions and market/emission data as they tend to vary according to the sources of CO 2 and geographical locations. The superstructure method along with a state-task network (STN) representation offers such flexibility in analyzing a CCUS system. This work proposes to use a STN representation of a process in a superstructure composed of feeds, processes, and products, to represent and optimize among various options of CCUS pathways through mathematical programming. A case study is conducted to illustrate the utility of the STN representation in the CCUS superstructure optimization.

关键词： Carbon capture carbon utilization superstructure state-task network representation mixed-integer programming techno-economic assessment carbon life cycle assessment

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A Mathematical Model for Optimization of Hospital Capacity in Response to Multiple Hazards: Case of Coquimbo and La Serena Territories in Chile

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Procedia Computer Science 2024年 251卷 801-806页

作者： Gustavo Gatica Erick Alexander Montenengro Fuentes Felipe Rojas Erwin Aliaga Laura Rivera Jairo R. Coronado-Hernandez Universdiad Andrés Bello Chile Universidad de la Costa Colombia

Socio-natural disasters pose a significant risk to healthcare systems, particularly in areas with high volcanic and seismic activity, combined with high poverty rates, reflecting vulnerable communities facing severe impacts on societal well-being and the economy. This is the case in the territories of Coquimbo and La Serena in Chile, which are constantly affected by natural phenomena, such as wildfires. Between 2020 and 2021, a total of 58 wildfires were recorded. This study presents a quantitative risk analysis of the healthcare network in response to the recurrence of wildfires in Coquimbo and La Serena cities, employing mixed-integer programming models for optimal location, relating fixed costs to the increased demand for care from the affected population. The methodology applied was quantitative, where the first phase involved identifying the areas affected by wildfires in La Serena and Coquimbo. Subsequently, we have formulated the mathematical model, including the objective function, definition of variables and parameters, definition of constraints, and finally, the implementation of the mathematical model's code.

关键词： Socio-natural disasters healthcare systems mixed-integer programming mathematical models fixed costs

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Comment on 'A simulation-based approach to price optimisation of the mixed bundling problem with capacity constraints'

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INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS 2017年 193卷 50-50页

作者： Luo, Xinggang Kwong, C. K. Tang, Jiafu Yu, Yang Hangzhou Dianzi Univ Sch Management Hangzhou Zhejiang Peoples R China Hong Kong Polytech Univ Dept Ind & Syst Engn Kowloon Hong Kong Peoples R China

Errors on the mathematical model of Mayer et al. (2013) are pointed out and corrected.

关键词： Pricing Bundling mixed-integer programming

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Operational planning of vehicles for rescue and relief operations considering the unavailability of the relocated vehicles

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SOCIO-ECONOMIC PLANNING SCIENCES 2023年第1期88卷

作者： Akbari, Leilanaz Kazemi, Ahmad Salari, Majid Ferdowsi Univ Mashhad Dept Ind Engn POB 91775-1111 Mashhad Iran Monash Univ Sch Math Melbourne Australia

Rapid urbanization has led to increasing fire incidents and false alarms, increasing the response time of fire departments. When a call arrives, the current technology deploys and relocates the vehicles based on their immediate impact on the system's preparedness. However, the unavailability of the relocated vehicles is often ignored during the relocation, thus the system's preparedness is overestimated. This paper presents a novel mixed-integer programming (MIP) model developed for the relocation and deployment of emergency/fire vehicles. The proposed model incorporates the unavailability element, and estimates system preparedness for future incidents more accurately than current models. To confirm the efficiency of the proposed approach, the required simulations were conducted in Mashhad, Iran. The results demonstrated the ability of the proposed model to improve the performance of the fire department in several performance metrics. We also provide sensitivity analysis over the critical parameters to demonstrate the robustness of the model.

关键词： Emergency services Simulation mixed-integer programming Deployment and relocation

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Minimizing the Density of Switch-Controller Latencies over Total Latency for Software-Defined Networks

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ALGORITHMS 2024年第9期17卷 393页

作者： Viveros, Andres Adasme, Pablo Dehghan Firoozabadi, Ali San Juan, Enrique Univ Santiago Chile Dept Elect Engn Ave Victor Jara 3519 Santiago 9170124 Chile Univ Tecnol Metropolitana Dept Elect Ave Jose Pedro Alessandri 1242 Santiago 7800003 Chile

This study examines the problem of minimizing the amount and distribution of time delays or latencies experienced by data as they travel from one point to another within a software-defined network (SDN). For this purpose, a model is proposed that seeks to represent the minimization of the distances between network switches in proportion to the total nodes in a network. The highlights of this study are the proposal of two mixed-integer quadratic models from a fractional initial version. The first is obtained by transforming (from the original fractional model) the objective function into equivalent constraints. The second one is obtained by splitting each term of the fraction with an additional variable. The two developed models have a relationship between switches and controllers with quadratic terms. For this reason, an algorithm is proposed that can solve these problems in a shorter CPU time than the proposed models. In the development of this research work, we used real benchmarks and randomly generated networks, which were to be solved by all the proposed models. In addition, a few additional random networks that are larger in size were considered to better evaluate the performance of the proposed algorithm. All these instances are evaluated for different density scenarios. More precisely, we impose a constraint on the number of controllers for each network. All tests were performed using our models and the computational power of the Gurobi solver to find the optimal solutions for most of the instances. To the best of our knowledge, this work represents a novel mathematical representation of the latency density management problem in an SDN to measure the efficiency of the network. A detailed analysis of the test results shows that the effectiveness of the proposed models is closely related to the size of the studied networks. Furthermore, it can be noticed that the performance of the second model compared to the first one presents better behavior in terms of CPU

关键词： latency density mixed-integer programming software-defined networking models and algorithms approaches

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Using infeasible path cuts to solve Electric Vehicle Routing Problems with realistic charging functions exactly within a branch-and-cut framework

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EURO JOURNAL ON TRANSPORTATION AND LOGISTICS 2024年 13卷

作者： Schulz, Arne Univ Hamburg Inst Operat Management Moorweidenstr 18 D-20148 Hamburg Germany

The paper investigates the Electric Vehicle Routing Problem with a non-linear concave and strictly monotonic increasing charging function. In the literature, the non-linear charging function is typically approximated by a piecewise linear charging function which does not overestimate the real charging function in any point. As the piecewise linear charging function underestimates the real state -of -charge in some points, such an approximation excludes feasible solutions from the solution space. To overcome this drawback we introduce a new method to determine a piecewise linear charging function overestimating the real charging function in a way that the area between both functions is minimized as well as an adaptation of a known linearization to include the piecewise linear charging function in a branch -and -cut approach. Thereby, we include infeasible solutions in the solution space. To declare them infeasible again we check every integer solution obtained in the branch -and -cut procedure and add an infeasible path cut if the solution is infeasible for the real charging function such that the procedure terminates with an optimal solution for the real charging function. Our approach is evaluated in a computational study in which instances with up to 100 customers were solved to optimality. Moreover, we evaluate the trade-off between a more complex model formulation due to more binary variables if the number of supporting points for the piecewise linear approximation is increased and the higher approximation error if fewer supporting points are used.

关键词： Electric Vehicle Routing Problem mixed-integer programming Branch-and-cut Infeasible path cuts

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