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Combinatorial Benders Cuts for the Minimum Tollbooth Problem

OPERATIONS RESEARCH 2009年第6期57卷 1510-1522页

作者： Bai, Lihui Rubin, Paul A. Valparaiso Univ Coll Business Adm Valparaiso IN 46383 USA Michigan State Univ Eli Broad Grad Sch Management E Lansing MI 48824 USA

We address a toll pricing problem in which the objective is to minimize the number of required toll facilities in a transportation network while inducing drivers to make the most efficient collective use of the network. We formulate the problem as a mixed-integer programming model and propose a solution method using combinatorial Benders cuts. Computational study of real networks as well as randomly generated networks indicates that our proposed method is efficient in obtaining provably optimal solutions for networks with small to medium sizes.

关键词： Benders decomposition branch and cut congestion pricing mixed-integer program traffic equilibrium

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Optimal resource allocation response to a smallpox outbreak

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COMPUTERS & INDUSTRIAL ENGINEERING 2013年第2期66卷 325-337页

作者： Ren, Yingtao Ordonez, Fernando Wu, Shinyi Univ So Calif Daniel J Epstein Dept Ind & Syst Engn Los Angeles CA 90089 USA Univ Chile Ind Engn Dept Santiago Chile

Infectious disease outbreaks, caused by nature or bioterrorism, are unfortunately very real threats to the general population. Planning an effective response to an infectious disease outbreak requires a coordinated effort in multiple locations to best allocate the limited resources. This decision problem is further complicated by the non-linear nature of disease propagation and the fact that outbreaks can jump urban, even national, boundaries. In this work we present a multi-city resource allocation model to distribute a limited amount of vaccine in order to minimize the total number of fatalities due to a smallpox outbreak. The model decides the amount of limited supplies to deliver and which infection control measure (isolation, ring, or mass vaccination) to use in each location in order to decrease the number of fatalities. The proposed model approximates the disease propagation dynamics in order to represent the problem as a mixed integer programming problem. Furthermore we develop an efficient heuristic to solve the resulting large scale mixed integer programming problem. Our results analyze the quality of the approximate disease propagation model and the efficiency of the heuristic algorithm. We also conduct a case study applying the multi-city model in planning an emergency response to a hypothetical national smallpox outbreak, which shows the possibility of saving a significant number of lives compared with a prorated allocation policy. (C) 2013 Elsevier Ltd. All rights reserved.

关键词： Infectious disease outbreak Vaccination policy Resource allocation Smallpox mixed-integer program

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A stochastic game-theoretic optimization approach for managing local electricity markets with electric vehicles and renewable sources

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APPLIED ENERGY 2024年 368卷

作者： Dolatabadi, Sayed Hamid Hosseini Bhuiyan, Tanveer Hossain Chen, Yang Morales, Jose Luis Univ Texas San Antonio Dept Mech Engn San Antonio TX 78249 USA North Carolina Agr & Tech State Univ Dept Ind & Syst Engn Greensboro NC USA Univ Texas San Antonio Dept Elect Engn San Antonio TX USA

In response to the growing need for sustainable and environmentally friendly energy ecosystems as well as the rapid adoption of electric vehicles (EVs) and renewable energy sources (RESs), local electricity markets (LEMs) offer a distinct potential to improve grid stability, promote clean energy, and reduce costs. However, harnessing the full potential of LEMs requires addressing multifaceted challenges associated with market dynamics, and the integration of EVs and RESs. Our study presents a stochastic bi-level model for managing LEMs, where the local transaction center (LTC) and other market participants (agents)-load aggregator (LA), charging station (CS), and their lower -level prosumers-aim to maximize their profits in a competitive game -theoretic structure. To ensure grid stability and profitability, LTC as the leader seeks to design a robust dynamic pricing strategy under uncertainty, whereas LA and CS, as followers, decide on the energy transaction amounts under uncertainty in their generation and consumption. We address several novel aspects of LEMs, such as heterogeneous behaviors of entities, uncertainties in renewable generation and load profiles, and the consumption profile of the EV fleet. We propose a centralized solution approach based on Karush-Kuhn-Tucker optimization and a decentralized approach based on a hybrid Genetic algorithm for solving the LEM management problem. The centralized approach provides optimal solutions whereas the decentralized approach provides near -optimal solutions much faster while maintaining the privacy of market participants (agents). Numerical results based on a realistic case study demonstrate that increasing the capacity of LTC's energy storage and its initial state of charge increases LTC's profit by 255%. Results also demonstrate that modeling the LEM under uncertainty as a twostage stochastic program provides a robust pricing decision resulting in a 433% higher profit compared to the deterministic modeling that ig

关键词： Two-stage stochastic program mixed-integer program Distribution grid Hierarchical market structure Hybrid Genetic algorithm

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Mobile parcel lockers with individual customer service

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NETWORKS 2023年第4期82卷 506-526页

作者： Koetschau, Rico Soeffker, Ninja Ehmke, Jan Fabian Univ Vienna Business Analyt Grp Vienna Austria Univ Vienna Business Analyt Grp Kolingasse 14-16 A-1090 Vienna Austria

The ongoing growth of e-commerce deliveries has led to a significant increase in last-mile delivery volumes. New technologies are being investigated to provide these deliveries efficiently and in a customer-friendly manner. A common practice is to use fixed parcel lockers (FPLs) to make deliveries independent from the presence of the customer as is the case in attended home deliveries (AHDs). FPLs are usually installed at key locations in cities, and customers can collect their package at any time once it has been delivered to this particular location. Mobile parcel lockers (MPLs) represent a new idea: they can be parked for temporary collection of items at different locations, keeping the pickup distance to the customer short and avoiding high infrastructure costs. However, customers need to collect their parcels within a restricted time window. This service is supposed to become especially efficient through autonomously operating vehicles that can move MPLs at low costs. In this article, we introduce the heterogeneous locker location problem to study the effects of fleets combining two of the services-FPLs, MPLs, AHDs-within one framework. In our comparison, we consider that customers may have different expectations regarding their maximum pickup distance as well as their temporal flexibility in accepting deliveries. A fixed fleet is applied to maximize the number of customers served, respecting individual customer preferences in terms of pickup distances and time windows. We evaluate the different delivery services regarding managerial insights on service quality and efficiency. In the experiments, we analyze the impact of structural demand differences and different fleet sizes, as well as the operational fleet utilization and the individual customer experience. Results show the potential to increase the number of customers served by about 14%-19% through the use of MPLs while considering individual customer preferences.

关键词： attended home delivery customer preferences heterogeneous locker location problem individual customer service last-mile delivery mixed-integer program mobile parcel locker parcel locker

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Expansion planning for waste-to-energy systems using waste forecast prediction sets

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NAVAL RESEARCH LOGISTICS 2016年第1期63卷 47-70页

作者： Wang, Shuming Ng, Tsan Sheng Wong, Manyu Univ Chinese Acad Sci Sch Econ & Management Beijing Peoples R China Natl Univ Singapore Dept Ind & Syst Engn Singapore 117548 Singapore

We consider an expansion planning problem for Waste-to-Energy (WtE) systems facing uncertainty in future waste supplies. The WtE expansion plans are regarded as strategic, long term decisions, while the waste distribution and treatment are medium to short term operational decisions which can adapt to the actual waste collected. We propose a prediction set uncertainty model which integrates a set of waste generation forecasts and is constructed based on user-specified levels of forecasting errors. Next, we use the prediction sets for WtE expansion scenario analysis. More specifically, for a given WtE expansion plan, the guaranteed net present value (NPV) is evaluated by computing an extreme value forecast trajectory of future waste generation from the prediction set that minimizes the maximum NPV of the WtE project. This problem is essentially a multiple stage min-max dynamic optimization problem. By exploiting the structure of the WtE problem, we show this is equivalent to a simpler min-max optimization problem, which can be further transformed into a single mixed-integer linear program. Furthermore, we extend the model to optimize the guaranteed NPV by searching over the set of all feasible expansion scenarios, and show that this can be solved by an exact cutting plane approach. We also propose a heuristic based on a constant proportion distribution rule for the WtE expansion optimization model, which reduces the problem into a moderate size mixed-integer program. Finally, our computational studies demonstrate that our proposed expansion model solutions are very stable and competitive in performance compared to scenario tree approaches. (c) 2016 Wiley Periodicals, Inc. Naval Research Logistics 63: 47-70, 2016

关键词： waste-to-energy systems expansion planning guaranteed NPV extreme value forecast adaptive min-max optimization mixed-integer program

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Two-stage dynamic model on allocation of construction facilities with genetic algorithm

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AUTOMATION IN CONSTRUCTION 2004年第4期13卷 481-490页

作者： Chau, KW Hong Kong Polytech Univ Dept Civil & Struct Engn Kowloon Hong Kong Peoples R China

By their very nature, activities within the construction site are generally highly dynamic and complex. Hence, it is highly desirable to be able to formulate the optimal strategy for allocating site-level facilities at different times of the project. The principal objective is to minimize the total cost, which comprises the transportation, handling, capital, and operating costs at potential intermediate transfer centers of various plant and material resources over the entire project duration. The problem can be formulated as a mixed integer program, which entails enormous computational effort for the solution, in particular when the problem size is large. In this paper, a two-stage dynamic model is developed to assist construction planners to formulate the optimal strategy for establishing potential intermediate transfer centers for site-level facilities such as batch plants, lay-down yards, receiving warehouses., various workshops, etc. Under this approach, the solution of the problem is split into two stages, namely, a lower-level stage and an upper-level stage. The former can be solved by a standard linear programming method, whereas the latter is solved by a genetic algorithm. The efficiency of the proposed algorithm is demonstrated through case examples. (C) 2004 Elsevier B.V. All rights reserved.

关键词： construction facilities dynamic resources allocation genetic algorithm mixed-integer program site planning two-stage formulation

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Optimal rebalancing and on-board charging of shared electric scooters

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TRANSPORTATION RESEARCH PART B-METHODOLOGICAL 2021年 147卷 197-219页

作者： Osorio, Jesus Lei, Chao Ouyang, Yanfeng Univ Illinois Dept Civil & Environm Engn Urbana IL 61801 USA Shanghai Maritime Univ Coll Transport & Commun Shanghai 201306 Peoples R China

This paper presents a sequence of models for optimal overnight charging and rebalancing of shared electric scooters (e-scooters) by allowing e-scooters to be charged while being transported on rebalancing vehicles. This problem is first modeled as a mixed-integer pro-gram for the multi-commodity inventory routing problem, where commodities represent e-scooters with different states of charge. To avoid prohibitive computation burden, contin-uous approximation techniques are proposed to estimate costs associated with the pickup and drop-off operations in small local neighborhoods, and the formulation turns into a discrete-continuous hybrid model for the integrated operations at both local and line-haul levels. A series of numerical experiments are conducted to demonstrate that, as compared to direct application of the discrete formulation, the proposed hybrid approach can pro-duce good quality solutions for large-scale instances in a much shorter computation time. (c) 2021 Elsevier Ltd. All rights reserved.

关键词： Electric scooter Sharing Micromobility mixed-integer program Continuous approximation

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Risk averse investment strategies for a private electricity generating company in a carbon constrained environment

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JOURNAL OF THE OPERATIONAL RESEARCH SOCIETY 2019年第12期70卷 2056-2068页

作者： Adiyeke, Esra Canakoglu, Ethem Agrali, Semra Bogazici Univ Dept Ind Engn Istanbul Turkey Bahcesehir Univ Dept Ind Engn Istanbul Turkey MEF Univ Dept Ind Engn Istanbul Turkey

We study a private electricity generating company that plans to enter a partially regulated market that operates under an active cap and trade system. There are different types of thermal and renewable power plants that the company considers to invest in over a predetermined planning horizon. Thermal power plants may include a carbon capture and storage technology in order to comply with the carbon limitations. We develop a time-consistent multi-stage stochastic optimization model for this investment problem, where the objective is to minimize the conditional value at risk (CV@R) of the net present value of the profit obtained through the planning horizon. We implement the model for a hypothetical generating company located in Turkey. The results show that the developed model is appropriate for determining risk averse investment strategies for a company that operates under carbon restricted market conditions.

关键词： Risk averse investments energy investment problems conditional value at risk mixed-integer program

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Combining population-based and exact methods for multi-level capacitated lot-sizing problems

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INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH 2006年第22期44卷 4755-4771页

作者： Pitakaso, Rapeepan Almeder, Christian Doerner, Karl F. Hartl, Richard F. Univ Vienna Dept Management Sci A-1210 Vienna Austria Ubonrahathanee Univ Dept Ind Engn Ubon Ratchathani 34190 Thailand

We present an ant-based algorithm to solve multi-level capacitated lot-sizing problems. We apply a hybrid approach where we use the ant system to optimize the decomposition of the problem into smaller subproblems. These subproblems, containing only a few items and periods, are solved using CPLEX. Then the overall solution is derived by consolidating the partial solutions. This hybrid approach provides superior results with respect to solution quality in comparison with the existing approaches in the literature.

关键词： ant colony optimization multi-level lot sizing material requirements planning problem decomposition mixed-integer program

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Planning Service Protocols for Extra-Long Trains with Transfers

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TRANSPORTATION SCIENCE 2024年第6期58卷 1167-1426, C2页

作者： Osorio, Jesus Shen, Shiyu Ouyang, Yanfeng Univ Illinois Urbana & Champaign Dept Civil & Environm Engn Urbana IL 61801 USA

This paper presents a modeling framework for optimizing operational protocols of extra-long trains (XLTs) in metro systems (i.e., trains longer than station platforms). With the rising travel demand in megacities, metro systems face challenges such as overcrowded stations, delays, and passenger anxieties. XLTs have been proposed as a promising solution to increase metro line capacity without additional infrastructure construction. The study explores the trade-offs between the additional capacity gained through complex protocols, the potential benefits of protocols with inline transfers, and the importance of effective passenger information systems from both passengers' and operators' perspectives. Mathematical programs are proposed to optimize protocols for a given demand distribution and to estimate the maximum line capacity of an XLT system. The benefits of implementing XLTs are evaluated in hypothetical and real-world cases with varying demand distributions and network sizes. The results demonstrate significant capacity increases ranging from 24% to 126% as compared with regular train operations, depending on system parameters and demand distribution. These findings demonstrate promise for using such systems to improve metro line capacity in the real world.

关键词： metro train time-tabling extra-long trains mixed-integer program network design planning

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