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Optimizing inland waterway port management decisions considering water level fluctuations

COMPUTERS & INDUSTRIAL ENGINEERING 2020年 140卷 106210-106210页

作者： Nur, Farjana Marufuzzaman, Mohammad Puryear, Stephen M. Mississippi State Univ Dept Ind & Syst Engn Starkville MS 39759 USA Mississippi State Univ CAVSE 153 Mississippi Pkwy Canton MS 39046 USA

This study presents a multi-commodity, multi-period mixed-integer linear programming model to efficiently manage the inland waterway port operations while minimizing the overall supply chain cost. An accelerated benders decomposition algorithm is developed to solve this challenging NP-hard problem. Proposed algorithm can produce high-quality solutions consistently within a reasonable amount of time. Numerical results show that considering water level fluctuations the test region is required to use an additional 81.5% barges and 39.7% towboats. Further, managerial insights are drawn for different key input parameters that impact port operations.

关键词： Inland waterway port Port optimization Barge management benders decomposition algorithm Local branching

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A benders based rolling horizon algorithm for a dynamic facility location problem

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COMPUTERS & INDUSTRIAL ENGINEERING 2016年第0期98卷 462-469页

作者： Marufuzzaman, Mohammad Gedik, Ridvan Roni, Mohammad S. Mississippi State Univ Dept Ind & Syst Engn Starkville MS 39759 USA Univ New Haven Dept Mech & Ind Engn 300 Boston Post Rd West Haven CT 06516 USA Idaho Natl Lab Biofuels & Renewable Energy Technol Idaho Falls ID 83415 USA

This study presents a well-known capacitated dynamic facility location problem (DFLP) that satisfies the customer demand at a minimum cost by determining the time period for opening, closing, or retaining an existing facility in a given location. To solve this challenging HP-hard problem, this paper develops a unique hybrid solution algorithm that combines a rolling horizon algorithm with an accelerated benders decomposition algorithm. Extensive computational experiments are performed on benchmark test instances to evaluate the hybrid algorithm's efficiency and robustness in solving the DFLP problem. Computational results indicate that the hybrid benders based rolling horizon algorithm consistently offers high quality feasible solutions in a much shorter computational time period than the standalone rolling horizon and accelerated benders decomposition algorithms in the experimental range. (C) 2016 Elsevier Ltd. All rights reserved.

关键词： Dynamic facility location problem benders decomposition algorithm Rolling horizon heuristics Hybrid benders based rolling horizon algorithm

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A Fast Solution Method for Stochastic Transmission Expansion Planning

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IEEE TRANSACTIONS ON POWER SYSTEMS 2017年第6期32卷 4684-4695页

作者： Zhan, Junpeng Chung, C. Y. Zare, Alireza Univ Saskatchewan Dept Elect & Comp Engn Saskatoon SK S7N 5A9 Canada

Stochastic programming is a cost-effective approach to model the transmission expansion planning (TEP) considering the uncertainties of wind and load, which is known as stochastic TEP (STEP). The uncertainty can be accurately represented by a large number of scenarios, which need to be reduced to a relatively small number in order to shorten the computational time required by the STEP. The forward selection algorithm (FSA) is an accurate scenario reduction method which, however, is quite time consuming. An improved FSA (IFSA) is proposed in order to shorten the computational time. The STEP is a large-scale mixed-integer programming problem, and, therefore, is difficult to be solved directly. benders decomposition algorithm is suitable to solve the STEP by decomposing it into master and multiple slave problems. The slave problems are nonlinear and thereby are difficult and time consuming to be solved. In this regard, a linearization method is proposed to solve the slave problems faster and to calculate the Lagrangian multipliers needed by the master problem. Two medium and a large datasets are used to demonstrate the efficiency of the IFSA and a 24-, a 300-, and a 2383-bus test systems are used to verify the efficiency of the linearization method.

关键词： benders decomposition algorithm Lagrangian multipliers linearization scenario reduction method stochastic programming transmission expansion planning (TEP)

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A robust model for recharging station location problem

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OPERATIONAL RESEARCH 2022年第4期22卷 4397-4440页

作者： Hosseini, Meysam Rahmani, Arsalan Hooshmand, F. Univ Kurdistan Dept Math Campus Bijar Sanandaj Iran Univ Kurdistan Fac Sci Dept Math Sanandaj Iran Amirkabir Univ Technol Dept Math & Comp Sci Tehran Polytech Tehran Iran

Due to the harmful effects of greenhouse gas emissions emitted by petroleum-based vehicles, the transition to alternative fuel vehicles, running on cleaner sources of energy such as electricity, is an important trend. At the beginning of the transition period to alternative-fuel vehicles, due to the lack of comprehensive recharging infrastructure, it is essential to optimally locate recharging stations so that the network is covered as much as possible. Most existing studies on this topic generally assume that the driving range of vehicles and the flow volume are known, however, in practice, they are highly stochastic. The first aim of this paper is to incorporate this type of uncertainty into the problem and formulate it as a robust scenario-based model in which the expected number of drivers who can complete their trip without running out of charge is maximized. The development of a solution algorithm, capable to solve large instances of the model, is another aim followed in this paper. Computational results over different instances taken from the literature or generated randomly confirm the efficiency of the proposed model and algorithms.

关键词： Electric vehicles Recharging station location Robust optimization Firefly algorithm benders decomposition algorithm

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A robust optimization approach for designing multi-period airport hub network with uncertain capacity

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ANNALS OF OPERATIONS RESEARCH 2024年 1-40页

作者： Hajiha, Mohammadmahdi Fathi, Michel Khakifirooz, Marzieh Pardalos, Panos M. Univ Arkansas Dept Ind Engn Fayetteville AR USA Univ North Texas G Brint Ryan Coll Business Dept Informat Technol & Decis Sci Denton TX 76203 USA Tecnol Monterrey Dept Ind Engn Monterrey 64849 NL Mexico Univ Florida Ctr Appl Optimizat Dept Ind & Syst Engn Gainesville FL 32611 USA

Airports are increasing their capacity to accelerate and facilitate travel and cargo delivery. At the same time, they aim to decrease expenses on delays caused by capacity overflow, encouraging policymakers to plan to enhance the capacity of crowded airports for the long term and set their transportation policies accordingly. This study develops a mathematical model for designing a network of airports with hub location problems (HLPs) with uncertain practical capacity in addition to their deterministic nominal capacity, using mixed integer programming (MIP). Our methodology proposes a robust optimization framework for uncertain capacity in hub airport facilities. Also, we utilize a practical approach for calculating the transit flow in hub airports by decomposing the flow into incoming, transiting, and outgoing statuses. We use a tailored benders decomposition algorithm (BDA) to facilitate the solution effort. Numerical results using data envelopment analysis (DEA) show a notable increase in the efficiency of the hub airports with the proposed method. Finally, airport managers can plan to improve the need for air transport infrastructure over a long period.

关键词： Airports network design Capacitated hub location problem Robust optimization Mixed integer programming benders decomposition algorithm Data envelopment analysis

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Mathematical Approach for Fleet Planning Under Complicated Circumstances

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Journal of Shanghai Jiaotong university(Science) 2014年第2期19卷 241-250页

作者：杨秋平张皞桑惠云谢新连 China Waterborne Transport Research Institute Transportation Management College Dalian Maritime University

In order to facilitate the scientific management of large-sized shipping companies, fleet planning under complicated circumstances has been studied. Based on multiple influencing factors such as the techno-economic status of ships, the investment capacity of company, the possible purchase of new ships, the buying/selling of second-hand vessels and the chartering/renting of ships, a mixed-integer programming model for fleet planning has been established. A large-sized shipping company is utilized to make an empirical study, and benders decomposition algorithm is employed to test the applicability of the proposed model. The result shows that the model is capable for multi-route, multi-ship and large-scaled fleet planning and thus helpful to support the decision making of large-sized shipping companies.

关键词： fleet planning mixed-integer programming benders decomposition algorithm

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A two-stage stochastic optimization model for port infrastructure planning

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MARITIME ECONOMICS & LOGISTICS 2024年第2期26卷 185-211页

作者： Bhurtyal, Sanjeev Hernandez, Sarah Eksioglu, Sandra Yves, Manzi Univ Arkansas 4190 Bell Engn Ctr Fayetteville AR 72701 USA Univ Arkansas Dept Ind Engn 4190 Bell Engn Ctr Fayetteville AR 72701 USA

This paper investigates inland port infrastructure investment planning under uncertain commodity (such as coal, petroleum, manufactured products, nonmetallic minerals) demand conditions. A two-stage stochastic optimization is developed to model the impact of demand uncertainty on infrastructure planning and transportation decisions. The model minimizes expected total costs, including capacity expansion costs, associated with handling equipment and storage infrastructure, and the expected transportation costs. To solve the problem, an accelerated benders decomposition algorithm is implemented. The use of a stochastic approach is justified by comparing the value of stochastic solution with its corresponding deterministic solution. For demonstration, the model is applied to the Arkansas section of the McClellan-Kerr Arkansas River Navigation System (MKARNS). Given data availability, the model is generalizable to other regions. Results show that as investment in port capacities (handling equipment and storage infrastructure) increases by $8 million, the percent of commodity volumes that moves via waterways (in ton-miles) increases by 1%. For the Arkansas application, the model determines nonmetallic minerals as the most affected commodity by investment, and it identifies a cluster of ports at Little Rock where the investment would have the most significant impact. The contribution of the paper is in introducing a stochastic modeling framework to quantify mode shift dependencies on inland waterways port infrastructure (handling equipment and storage). Comparison of a stochastic approach to the state-of-the-literature deterministic approaches, shows that a failure to use a stochastic modeling to capture uncertainty in commodity demand could cost up to $21 M per year. The model serves as a decision-making tool for optimal, distributed allocation of monetary investments, that encourages mode shift to inland waterways.

关键词： Inland waterway port benders decomposition algorithm Stochastic programming Port infrastructure investment

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Research on Source-load Coordinated Optimal Scheduling of Integrated Energy System 9

Research on Source-load Coordinated Optimal Scheduling of In...

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9th International Forum on Electrical Engineering and Automation (IFEEA)

作者： Zhou, Dongxu Zhu, Zhengyi State Grid Jiangsu Elect Power Co Ltd Nanjing Power Supply Branch Nanjing Peoples R China

ISBN: (纸本)9781665464215

With the penetration of renewable energy such as wind and photovoltaic in the energy system, the intermittent and fluctuating nature of their output leads to the uncertainty of energy supply of the energy system, and the modeling and optimal scheduling of the energy system face great challenges. Aiming at the above problems, this paper constructs a source-load coordinated optimal scheduling model for the integrated energy system. The model takes into account the uncertainty of the system scenery output and the variable working conditions of system equipment, and it uses the benders decomposition algorithm and the alternating direction multiplier method (ADMM) to solve the model, realizing the cooperative optimal scheduling of source-load on both sides. Finally, the proposed method is tested in a community in Nanjing, and the results show that the proposed method can promote the positive source-load interaction and improve the economy, environmental protection and stability of system operation.

关键词： integrated energy system variable working condition source-load co-optimization benders decomposition algorithm alternating direction multiplier method

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A New Model for Sea-Rail Intermodal Transportation Network System Planning Considering the Arctic Route 4

A New Model for Sea-Rail Intermodal Transportation Network S...

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4th International Conference on Intelligent Autonomous Systems (ICoIAS)

作者： Han, Peixiu Sun, Zhuo Liu, Kaili Li, Bin Dalian Maritime Univ Coll Transportat Engn Dalian Peoples R China BMW Brilliance Auto Co Ltd Dept Supply Chain Shenyang Peoples R China

ISBN: (纸本)9781665441957

The opening of the Arctic route will greatly shorten the distance of navigation and save costs. This research was mainly focus on hierarchical hub locations for rail-sea container transportation network system planning considering the Arctic Route. According to the characteristics of integrated network including the Arctic route, a new mathematical model was established by juxtaposing the traditional idea of hierarchical hub and hub arc location. benders decomposition method was used to transform and solve the mixed integer nonlinear model. Based on the analysis of the Arctic route example, it could be indicated that the number of central hubs directly affects the transportation cost and location of hubs. This study provides a certain direction for a shipping company to choose hubs after the opening of the Arctic route in the future and also made sense for the rail-sea intermodal transportation system from a strategic consideration.

关键词： rail-sea transportation system planning the Arctic Route Hierarchical hub location benders decomposition algorithm

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Robust vehicle-to-grid power dispatching operations amid sociotechnical complexities

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APPLIED ENERGY 2021年 281卷 115912-115912页

作者： Jiao, Zihao Ran, Lun Zhang, Yanzi Ren, Yaping Beijing Technol & Business Univ Sch Int Econ & Management Beijing 100048 Peoples R China Beijing Inst Technol Sch Management & Econ Beijing 100081 Peoples R China Sustainable Dev Res Inst Econ & Soc Beijing Beijing 100081 Peoples R China Tsinghua Univ Dept Ind Engn Beijing 100084 Peoples R China Jinan Univ Sch Intelligent Syst Sci & Engn Zhuhai Campus Zhuhai 519000 Guangdong Peoples R China

The technical and social complexities that characterize electric vehicle owners and the power market degrade the positive impacts of the emerging vehicle-to-grid technique. Motivated by sociotechnical challenges in practical V2G operations, we aim to design an efficient EV charging and discharging scheduling strategy to improve the reliability and profitability of V2G operations. Specifically, we propose a robust model to optimize V2G charging and discharging scheduling. Without requiring full information regarding the distribution data, our methodology framework, which adopts a distributed robust optimization framework, facilitates V2G aggregators to address operational uncertainties such as users' travel demands. We adopt a benders decomposition algorithm to handle the intractable nonlinear robust counterparts. Our linear approximation of the nonlinear BD subproblem is more effective at reducing the solution complexity than previous research. A case study in CAR2GO in Amsterdam, with 12 service region and three months of travel demand data, reveal that: (1) The adverse impacts on the power dispatching cost, caused by the Range Anxiety in the vehicle-to-grid operations, are mitigated by adopting our integrated policy compared with the traditional deterministic method. (2) By adopting the proposed policy and decomposition algorithm, vehicle-to-grid aggregator benefits through lower operational costs and near 76.74% decision efficiency improvement under the large-scale dispatching programming. (3) Vehicle-to-grid aggregator, the government should be prudent to design a power dispatching plan by considering the range anxiety and battery durability for their significant impacts on the reliable service, environment, and cost control.

关键词： Sustainable operations Robust optimization Distributed robust optimization Vehicle-to-grid operations benders decomposition algorithm

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