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A Decomposition-Based Heuristic Method for Inventory Routing Problem

IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS 2022年第10期23卷 18352-18360页

作者： Wang, Shijin Chu, Feng Fuzhou Univ Sch Econ & Management Dept Management Sci & Engn Fuzhou 350116 Peoples R China Univ Paris Saclay Univ Evry Lab IBISC F-91025 Evry France

The inventory routing problem (IRP) arises in a broad spectrum of real-life applications related to joint decisions of inventory and routing. In the basic IRP, a supplier has to make decisions about the delivery timing, delivered quantity of a single product and routing with a single vehicle to a set of retailers without backlog. It poses computational challenge due to its natural complexity. To tackle this problem, we propose a two-phase decomposition-based heuristic method. In Phase 1, a logic-based Benders like decomposition method is employed to first determine the retailers' replenishments, followed by the routing decisions individually for each period. Valid cuts, inequalities for diversification constraints and for greedy search are employed. Then, the solutions obtained in Phase 1 are improved with a restricted mixed integer linear programming (MILP) model in Phase 2. Computational experiments are conducted on 220 benchmark problem instances with up to 200 retailers and 6 periods. The results show the high performance of the proposed method and it is comparable to the state-of-the-art heuristics in terms of both efficiency and effectiveness.

关键词： Routing Costs Transportation Production linear programming Hair Timing Inventory routing problem mixed integer linear programming decomposition-based heuristic logic-based Benders like decomposition

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Hybridization of NSGA-II and MILP for optimization of the location of electric-scooters sharing-stations

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IEEE LATIN AMERICA TRANSACTIONS 2022年第11期20卷 2381-2387页

作者： Gabriel Baquela, Enrique Carolina Olivera, Ana Univ Tecnol Nacl UTN Grp Invest Simulac & Optimizac Ind GISOI Dept Ingn Ind Fac Reg San Nicolas FRSN Colon 332B2900LWH Buenos Aires DF Argentina Univ Nacl Cuyo Inst Tecnol Informac & Comunicac CONICET Padre Jorge Contreras 1300M5502JMA Mendoza Argentina Univ Nacl Cuyo Fac Ingn M5502JMA Mendoza Argentina

TA crucial aspect of the proper functioning of bikes and electric scooters sharing systems is the correct locationand dimensioning of the sharing stations. The resolution of the previous problem is carried out based on the maximization of coverage or the minimization of costs, but the two objectives are not usually treated at the same *** this work, we propose a method based on the hybridization of the popular Elitist Non-Dominated Sorting Genetic Algorithm (NSGA- II) with a mixed-integer linear programming (MILP) model to approximate the Pareto Frontier of the problem. This allows the decision-maker a greater understanding of the range of possible options. The NSGA-II plays the role of an outer block that deals with the selection and sizing of each of sharing stations. The MILP model is an inner block that calculates the associated coverage of that solution. The schema was compared with an adaptative-weighting algorithm, reaching the hybridization of NSGA-II and MILP a better coverage of the Pareto Frontier.

关键词： Genetic algorithms IEEE transactions Transportation Sorting Silicon Motorcycles mixed integer linear programming Multi-Objective mixed-integer linear programming Meta-heuristics Math-heuristics E-Scooters Sustainable Transportation

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Artificial neural networks integrated mixed integer mathematical model for multi-fleet heterogeneous time-dependent cash in transit problem with time windows

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NEURAL COMPUTING & APPLICATIONS 2022年第24期34卷 21891-21909页

作者： Ayyildiz, Ertugrul Taskin, Alev Yildiz, Aslihan Ozkan, Coskun Karadeniz Tech Univ Dept Ind Engn Trabzon Turkey Yildiz Tech Univ Dept Ind Engn Istanbul Turkey

The cash in transit (CIT) problem is a version of the vehicle routing problem (VRP), which deals with the planning of money distribution from the depot(s) to the automated teller machines (ATMs) safely and quickly. This study investigates a novel CIT problem, which is a variant of time-dependent VRP with time windows. To establish a more realistic approach to the time-dependent CIT problem, vehicle speed varying according to traffic density is considered. The problem is formulated as a mixed-integer mathematical model. Artificial neural networks (ANNs) are used to forecast the money demand for each ATM. For this purpose, key factors are defined, and a formulation is proposed to determine the money deposited to and withdrawn into ATMs. The mathematical model is run for different scenarios, and optimum routes are obtained.

关键词： Artificial neural networks Cash in transit mixed integer linear programming Time-dependent vehicle routing problem

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Reliable routing in Wireless Body Area Network using optimum number of relay nodes for enhancing network lifetime

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JOURNAL OF AMBIENT INTELLIGENCE AND SMART ENVIRONMENTS 2022年第2期14卷 135-153页

作者： Adhikary, Sriyanjana Chattopadhyay, Samiran Ghosh, Biswajit Choudhury, Sankhayan Nath, Shubha Brata Garain, Nilkantha Jadavpur Univ Dept Informat Technol Kolkata India TCG Ctr Res & Educ Sci & Technol Inst Adv Intelligence Hoskote India Univ Engn & Management Kolkata Dept Comp Sci & Engn Kolkata India Calcutta Univ Dept Comp Sci & Engn Kolkata India Indian Inst Technol Kharagpur Dept Comp Sci & Engn Kharagpur India

Wireless Body Area Network (WBAN) is an emerging technology that has the potential to redefine healthcare sector around the world. It can perform proactively by ubiquitously monitoring human health. But its enormous scope is challenged by limited battery power of the sensors, energy and bandwidth. Moreover, the random motion of human beings makes sensor positioning difficult and restricts efficiently routing of critical health parameter values. State of the art protocols do not address the adverse effects of heating of the implanted sensors on human tissues along with energy constraints and interference issues simultaneously. This paper handles all these issues jointly by designing a topology which has an optimized number of relay nodes and then proposes an efficient routing algorithm. Relay nodes are incorporated to frame the backbone of the connected wireless network so that all sensor nodes are coupled with at least one relay node and none of the nodes in the network remain isolated. In the proposed method, the remaining energy of the in-vivo sensors are dissipated intelligently and homogeneously so that network lifetime is enhanced without compromising reliability. Moreover, in our method, multicasting has been used to reduce transmission of unnecessary packets. Our design also leads to minimum hop count from body sensors to the sink node. The effectiveness and feasibility of our proposed approach has been evaluated and analyzed through numerous simulations. The analysis illustrates the efficacy of the proposed solution in terms of delay, network lifetime, energy efficiency, SAR and throughput.

关键词： Wireless Body Area Network routing mixed integer linear programming energy minimization interference relay node

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An improved genetic algorithm for flexible job shop scheduling problem considering reconfigurable machine tools with limited auxiliary modules

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JOURNAL OF MANUFACTURING SYSTEMS 2022年 62卷 650-667页

作者： Fan, Jiaxin Zhang, Chunjiang Liu, Qihao Shen, Weiming Gao, Liang Huazhong Univ Sci & Technol State Key Lab Digital Mfg Equipment & Technol Wuhan Peoples R China

Reconfigurable manufacturing system is widely regarded as a major drive towards the next-generation manufacturing, where one of the most common scenarios is that advanced reconfigurable machine tools (RMT) are equipped with auxiliary modules (AM) to improve the production flexibility, thus rapidly responding to market demands. Production scheduling is facing great challenges in this situation, because the limited number of AMs becomes the primary difficulty for the resource allocation. This paper investigates a flexible job shop scheduling problem with machine reconfigurations (FJSP-MR) to minimize the total weighted tardiness (TWT). Firstly, a sequence-based mixed integer linear programming (MILP) model is established for the FJSPMR. Afterwards, considering the characteristics of the AM selection sub-problem, an improved genetic algorithm (IGA) with problem-specific encoding and decoding strategies is developed, in which an iterated local search with a modified k-insertion neighborhood structure is introduced for further optimization. Critical paths for the less common TWT objective are fully considered to ensure the local search is performed on bottlenecks of incumbent solutions. The proposed MILP model and IGA are tested on three groups of instances extended from public benchmark sets. Numerical experimental results indicate that the proposed IGA is highly efficient for the FJSP-MR in a variety of scenarios, where the specially designed local search is an effective complementary component for the basic genetic algorithm. Furthermore, a real-world FJSP-MR case is studied to show the proposed IGA is applicable to large-scale engineering problems.

关键词： Reconfigurable manufacturing systems Flexible job shop scheduling Reconfigurable machine tools Auxiliary modules mixed integer linear programming Improved genetic algorithm

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Modeling Spinning Reserve Contribution Using Physical Ramp Rates

Modeling Spinning Reserve Contribution Using Physical Ramp R...

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IEEE-Power-and-Energy-Society General Meeting (PESGM)

作者： Zhang, Shubo Meyer, John L. Harjunkoski, Iiro Moslehi, Khosrow Kumar, Pradip G. Hitachi Energy Hitachi Ibaraki Japan

ISBN: (纸本)9781665464413

As part of administering the day-ahead and real-time wholesale electricity markets, the New York Independent System Operator (NYISO) is responsible for scheduling adequate operating reserve is available for generator outage contingencies. This paper proposes a Ramp Rate Dependent (RRD) reformulation of spinning reserve scheduling that can utilize Multiple Response Rates (MRR) across the Combined Cycle Gas Turbine (CCGT) generator's range of output. Tests are conducted on NYISO's market simulator. Results have shown that operating reserve scheduled by the proposed approach better reflects the operating characteristics of CCGTs. The increase in model complexity has minimal economic impact, negligible performance degradation and is scalable to face the increasing flexibility in NYISO's electricity and ancillary service market.

关键词： unit commitment economic dispatch combined cycle gas turbine operating reserve ramp rate mixed integer linear programming

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Optimizing the Maintenance Schedule of a Combined Cycle Gas Turbine Considering Different Maintenance Types and Operating Hours

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IEEE ACCESS 2022年 10卷 98872-98881页

作者： Yu, Vincent F. Lin, Yueh-Sheng Jodiawan, Panca He, Meng-Duo Lin, Shih-Wei Natl Taiwan Univ Sci & Technol Dept Ind Management Taipei 106 Taiwan Natl Taiwan Univ Sci & Technol Ctr Cyber Phys Syst Innovat Taipei 106 Taiwan Chang Gung Univ Dept Informat Management Taoyuan 333 Taiwan Keelung Chang Gung Mem Hosp Dept Emergency Med Keelung 204 Taiwan Ming Chi Univ Technol Dept Ind Engn & Management New Taipei 243 Taiwan

An efficient maintenance schedule for gas turbines of power plants ensures a reliable electricity supply. This study addresses a generator maintenance scheduling problem arising from Taiwan's combined cycle power plant with two notable characteristics, i.e., a specific sequence of various maintenance types and the concept of performing maintenance according to operational hours spent. The objective is to minimize the total maintenance cost. The problem is formulated as a mixed integer linear Program which is solvable by an off-the-shelf exact solver, i.e., CPLEX. Moreover, a set of newly generated instances is proposed as benchmark instances for the problem. The instances generated are based on the realistic conditions obtained from the historical record of Taiwan's combined cycle power plant. Computational studies are presented as interesting insights regarding the complexity of the problem and the factors driving the total maintenance costs.

关键词： Maintenance engineering Generators Turbines Task analysis Costs Power generation Mathematical models Industrial plants mixed integer linear programming Power generation Combined cycle power plant generator maintenance scheduling mixed integer linear programming

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Autonomous bus timetable synchronization for maximizing smooth transfers with passenger assignment

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EXPERT SYSTEMS WITH APPLICATIONS 2022年第0期193卷 116430-116430页

作者： Wang, Yun Zhou, Yu Yan, Xuedong Beijing Jiaotong Univ Sch Traff & Transportat MOT Key Lab Transport Ind Big Data Applicat Techn 3 Shang Yuan Cun Beijing 100044 Peoples R China Natl Univ Singapore Dept Civil & Environm Engn Singapore 117576 Singapore

Autonomous bus (AB), as a major component of public transport systems in the future, are expected to positively impact safety, congestion, private car ownership, energy consumptions, and CO2 emissions. The adoption of ABs will inevitably bring a magnitude of changes and revolutions for the traditional bus operations. This paper investigates the AB timetable synchronization problem (AB-TSP), which involves both the AB timetabling and the passenger assignment. The AB-TSP is first formulated as mixed integer nonlinear programming (MINLP) and then converted to an equivalent mixed integer linear programming (MILP). Two families of valid inequalities are proposed based on the property of the developed model in order to accelerate the solution process. A numerical example on a medium-size AB network shows the effectiveness and efficiency of the valid inequalities, and we also make a detailed comparison between the AB-TSP and the traditional bus timetable synchronization problem (TB-TSP). Finally, a genetic algorithm (GA) framework is designed to cope with the large-scale AB-TSP, and the results of a case study based on the Tower Transit SG bus network show that the intractable real-world problem can also obtain satisfactory solutions within a reasonable computation time.

关键词： Autonomous bus Timetable synchronization Passenger assignment mixed integer linear programming Valid inequalities Genetic algorithm

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A rough cut cybersecurity investment using portfolio of security controls with maximum cybersecurity value

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INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH 2022年第21期60卷 6556-6572页

作者： Sawik, Tadeusz Sawik, Bartosz Reykjavik Univ Dept Engn IS-101 Reykjavik Iceland AGH Univ Sci & Technol Dept Operat Res Krakow Poland Univ Publ Navarra Dept Stat Comp Sci & Math Pamplona Spain Univ Calif Berkeley Haas Sch Business Berkeley CA 94720 USA AGH Univ Sci & Technol Dept Business Informat & Engn Management Krakow Poland

This paper deals with optimisation of cybersecurity investment in supply chains using stochastic programming approach. A classical exponential function of breach probability and the intuitive idea of 'the expected net benefits', originally presented in 2002 by Gordon and Loeb, were applied to introduce the concept of cybersecurity value. The cybersecurity value of security control is defined as the value gained by implementing a single control to secure a subset of components. The cybersecurity value of a control can be seen as a measure of its efficiency in reducing vulnerability of a secured system or component. A mixed binary optimisation problem, next transformed into an unconstrained binary program is developed to maximise total cybersecurity value of control portfolio. The optimal solution to the binary program provides a simple formula to immediately obtain the portfolio of security controls with maximum total cybersecurity value and determine a rough cut cybersecurity investment. This study also shows that portfolio of security controls with maximum total cybersecurity value reduces the losses from security breaches and mitigate the impact of cyber risk.

关键词： Cybersecurity of supply chains cybersecurity investment security control portfolio mixed integer linear programming unconstrained binary program

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Integration of a novel distributed water and energy system in the oilfield

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CHEMICAL ENGINEERING RESEARCH & DESIGN 2022年 186卷 350-361页

作者： Li, Zhuochao Guo, Yi Xu, Ning Wang, Bohong Zhong, Rongqiang Li, Wenlong Liang, Yongtu China Univ Petr Beijing Key Lab Urban Oil & Gas Distribut Technol Fuxue Rd 18 Beijing 102249 Peoples R China Sinopec Inst Petr Engn & Technol Northwest Oil Field Branch Urumqi 830011 Xinjiang Peoples R China Zhejiang Ocean Univ Natl & Local Joint Engn Res Ctr Harbor Oil & Gas S Zhejiang Key Lab Petrochem Environm Pollut Control 1 Haida South Rd Zhoushan 316022 Peoples R China

The oil production process in union stations requires consuming a lot of energy, and sewage at high temperature will be produced simultaneously. Realizing the benefits of energy saving that waste heat utilization can bring to the oil field, this article first de-scribes a novel integrated water separation and treatment process (IWSTP) with energy -saving effects. Based on the integrated process, the oilfield distributed heat station system is a good choice for utilizing waste heat from sewage. The heat pump is also considered as indispensable equipment for recovering the low-temperature waste heat of oilfield sewage. Next, a mixed integer linear programming model considering energy and tech-nical constraints is developed to optimize the oilfield water treatment process to mini-mize annual total cost, which determines the selection and capacity of the required equipment. Taking an oilfield in China as an example, the validity and applicability of this model are demonstrated. The results show that the optimized scheme saves 14.08% of the economic cost compared with the traditional energy supply scheme. Finally, the impact of energy price fluctuation on the design results is analyzed. (c) 2022 Institution of Chemical Engineers. Published by Elsevier Ltd. All rights reserved.

关键词： Water treatment Energy saving Oil production mixed integer linear programming

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