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Cost-effective planning and abatement costs of battery electric passenger vessel services

TRANSPORTATION RESEARCH PART D-TRANSPORT AND ENVIRONMENT 2022年 113卷

作者： Havre, Hakon Furnes Lien, Ulrik Ness, Mattias Myklebust Fagerholt, Kjetil Rodseth, Kenneth Lovold Norwegian Univ Sci & Technol Dept Ind Econ & Technol Management Trondheim Norway Inst Transport Econ Gaustadalleen 21 NO-0349 Oslo Norway

This paper analyzes the energy replacement potential for high-speed passenger vessels. Emphasis is on whether better planning of services can mitigate technical and economic barriers to zero emission transport. A novel mixed-integer programming problem for battery electric vessel services that jointly minimizes operator and passenger costs subject to strategic (fleet selection and land-based infrastructure location), tactical (frequency), and operational decisions (sailing pattern) is proposed. The planning problem is utilized to estimate technology replacement potential and associated costs for two existing services/routes in Norway and based on four hypothetical demand scenarios derived from the same two services. The results showcase that constraints related to battery range and charging limit the replacement potential and make energy conservation more pertinent. Abatement cost estimates range between 3 000 and 18 000 NOK per ton CO2, placing them well above the social cost of carbon calculated at 2 000 NOK per ton by 2030.

关键词： High-speed passenger vessels Zero emissions Marine battery mixed-integer programming

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Sustainable container distribution by alternatively fueled vehicles under customer and technical constraints

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IFAC-PapersOnLine 2022年第10期55卷 836-841页

作者： Sezgi Tekil-Ergün Erwin Pesch Katarzyna Anna Kuzmicz Institute of Information Systems Faculty III University of Siegen Siegen Center for Advanced Studies in Management HHL Leipzig Graduate School of Management Leipzig Germany Faculty of Engineering Management Bialystok University of Technology Bialystok Poland

The scale of freight forwarding to the hinterland becomes an issue from the perspective of both – transport policy and cost efficiency of service providers. This problem is sharply visible in areas where ports, depots, inland intermodal terminals, exporters and importers are located, and full and empty containers satisfying demand and supply are frequently distributed creating a lot of traffic. Therefore solutions meeting the challenges of sustainable transport, responding to climate change and regulation of CO2 emissions are in need. In this paper, a variant of a mixed Fleet Heterogeneous Dial-a-Ride Problem is proposed for optimal routing of trucks carrying full and empty 20-foot and 40-foot containers, with multiple pick-ups and deliveries. Transportation is performed by alternatively fueled vehicles (AFVs) for environmental reasons which causes a constraint of a limited driving range and a need of refueling. The main objective is minimising the total distance subject to matching the empty container demand and supply, necessary refueling of the trucks, and service time windows.

关键词： heterogeneous dial-a-ride problem full empty container transportation green vehicle routing problem mixed-integer programming Lagrange relaxation

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Routing decisions of a hybrid vehicle on electric road networks

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IFAC-PapersOnLine 2022年第10期55卷 227-232页

作者： Alejandro Gutierrez-Alcoba Roberto Rossi Belen Martin-Barragan Tim Embley Business School University of Edinburgh Edinburgh UK Costain Group Plc. Maidenhead UK

An electric road system (ERS) is a road in which vehicles can travel powered from the electrical grid. Deployed at scale, this technology reduces or eliminates the need for electric vehicles (EVs) to stop for recharging, and allows for equipping these vehicles with smaller batteries. In particular, it facilitates the decarbonisation of road freight transportation. In this paper, we present a routing problem for a hybrid vehicle travelling on a ERS road network, using estimations of power requirements of the vehicle. We formulate the problem as a mixed integer linear and use it to present numerical experiments on a road network electrified in three stages, showing how the technology can help reducing fuel usage and have a global impact on how the roads in the network are used.

关键词： Freight transportation Electric Vehicles mixed-integer programming Routing scheduling Fuel consumption Emission reduction Refueling Electric battery capacity limitation

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Optimal assignment for the single-household shared autonomous vehicle problem

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TRANSPORTATION RESEARCH PART B-METHODOLOGICAL 2020年 141卷 98-115页

作者： Cokyasar, Taner Larson, Jeffrey Argonne Natl Lab Energy Syst Div Argonne IL 60439 USA Argonne Natl Lab Math & Comp Sci Div Argonne IL 60439 USA

Autonomous vehicles have the potential to transform the way people are transported. While driverless technology may mean fewer vehicles are required to transport people to and from their daily activities, such changes may result in increased congestion or total miles traveled. In this study, we solve the single-household shared autonomous vehicle problem to identify cost-optimal routings of vehicles throughout the day. Such a tool will be useful for consumers seeking to minimize cost and for regulators seeking to understand and predict how people may behave in different scenarios. We provide a thorough literature review and construct a mixed-integer linear program to minimize the daily travel cost of a household attending a given set of activities. Since solution time is a determinant for applicability of such a model, we present the model in a component-wise fashion. This approach allows us to understand which features most affect the problem complexity and solution time. We note that modeling carpooling is the feature that most increases time to find an optimal solution, and we therefore propose a novel modeling technique for carpooling two people. We illustrate the performance of our model by comparing it with other models from the literature and note that our model can solve significantly larger problem instances and in a time that is short enough to facilitate real-time scheduling. We also highlight the utility of our model for regulators, who can use it to analyze quickly produced optimal routes under different cost/tax scenarios. (C) 2020 Elsevier Ltd. All rights reserved.

关键词： Autonomous vehicle routing mixed-integer programming Operational decision-making

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A continuous-time supply-driven inventory-constrained routing problem

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OMEGA-INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE 2020年第0期92卷 102151-000页

作者： Fokkema, Jan Eise Land, Martin J. Coelho, Leandro C. Wortmann, Hans Huitema, George B. Univ Groningen Fac Econ & Business Dept Operat POB 800 NL-9700 AV Groningen Netherlands Univ Laval Fac Adm Sci Operat & Decis Syst Dept Quebec City PQ Canada

We address an inventory routing problem (IRP) in which routing and inventory decisions are dictated by supply rather than demand. Moreover, inventory is held in containers that act as both a storage container and a movable transport unit. This problem emanates from logistics related to biogas transportation in which biogas is transported in containers from many suppliers to a single facility. We present a novel and compact formulation for the supply-driven IRP which addresses the routing decisions in continuous-time in which inventory levels within the containers are continuous. Valid inequalities are included and realistic instances are solved to optimality. For all experiments, we found that the total transportation time is minimized when the storage capacity at each supplier is larger than or equal to the vehicle capacity. These routes are characterized by tours in which mostly single suppliers are visited. In 95% of the instances, the average content level of the exchanged containers exceeded 99.6%. (C) 2019 Elsevier Ltd. All rights reserved.

关键词： Inventory routing Continuous time mixed-integer programming Supply-driven

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An exact algorithm for robust influence maximization

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MATHEMATICAL programming 2020年第1-2期183卷 419-453页

作者： Nannicini, Giacomo Sartor, Giorgio Traversi, Emiliano Calvo, Roberto Wolfler IBM TJ Watson Res Ctr Yorktown Hts NY 10598 USA SINTEF Digital Oslo Norway Univ Sorbonne Paris Nord LIPN CNRS UMR 7030 F-93430 Villetaneuse France Univ Cagliari Dept Math & Comp Sci Cagliari Italy

We propose a Branch-and-Cut algorithm for the robust influence maximization problem. The influence maximization problem aims to identify, in a social network, a set of given cardinality comprising actors that are able to influence the maximum number of other actors. We assume that the social network is given in the form of a graph with node thresholds to indicate the resistance of an actor to influence, and arc weights to represent the strength of the influence between two actors. In the robust version of the problem that we study, the node thresholds and arc weights are affected by uncertainty and we optimize over a worst-case scenario within given robustness budgets. We study properties of the robust solution and showthat even computing theworst-case scenario for given robustness budgets is NP-hard. We implement an exact Branch-and-Cut as well as a heuristic Branch-Cut-and-Price. Numerical experiments show that we are able to solve to optimality instances of size comparable to other exact approaches in the literature for the non-robust problem, and we can tackle the robust version with similar performance. On larger instances (= 2000 nodes), our heuristic Branch-Cutand-Price significantly outperforms a 2-opt heuristic. An extended abstract of this paper appeared in the proceedings of IPCO 2019.

关键词： Influence maximization mixed-integer programming Robust optimization

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Exploiting Sparsity in SDP Relaxation for Harmonic Balance Method

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IEEE ACCESS 2020年 8卷 115957-115965页

作者： Yang, Cheng-Hsiung Deng, Ben Shen Natl Taiwan Univ Sci & Technol Grad Inst Automat & Control Taipei 10607 Taiwan Natl Taiwan Univ Sci & Technol Ctr Cyber Phys Syst Innovat Taipei 10607 Taiwan

In general, harmonic balance problems are extremely nonconvex and difficult to solve. A convex relaxation in the form of semidefinite programming has attracted a lot of attention recently, as it finds a global solution with high accuracy without the need for initial values. However, the computational cost of solving large-scale optimization poses a major challenge for the application in many real-world practical cases. This work proposes a heuristic optimization approach to find the Fourier coefficients of harmonic balance problems. The structural sparsity in the Harmonic Balance problem is exploited to improve numerical tractability and efficiency at the cost of adding smaller-sized semidefinite constraints in the problem formulation. After exploiting sparsity, the simulation results show that the size of the largest semidefinite constraint and the number of decision variables are greatly reduced. In addition, the computation speed shows an improvement rate of 3 or 7.5 times for larger instance problems and a reduction in memory occupation. Moreover, the proposed formulation can also solve nonlinear circuits with nonpolynomial nonlinearities with high accuracy.

关键词： Harmonic analysis Optimization Frequency-domain analysis programming Time-domain analysis Nonlinear systems Fourier series Harmonic balance method mixed-integer programming nonlinear circuits periodic solutions steady-state problems

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MIDAS: A mixed integer dynamic approximation scheme

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MATHEMATICAL programming 2020年第1期181卷 19-50页

作者： Philpott, A. B. Wahid, F. Bonnans, J. F. Univ Auckland Elect Power Optimizat Ctr Auckland New Zealand Artelys Consulting Paris France Ecole Polytech INRIA Saclay France

mixed integer dynamic approximation scheme (MIDAS) is a new sampling-based algorithm for solving finite-horizon stochastic dynamic programs with monotonic Bellman functions. MIDAS approximates these value functions using step functions, leading to stage problems that are mixed integer programs. We provide a general description ofMIDAS, and prove its almost-sure convergence to a 2T e-optimal policy for problems with T stages when the Bellman functions are known to be monotonic, and the sampling process satisfies standard assumptions.

关键词： Stochastic programming Approximate dynamic programming Sampling mixed-integer programming

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Production scheduling problem in a factory of automobile component primer painting

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JOURNAL OF INTELLIGENT MANUFACTURING 2020年第6期31卷 1483-1496页

作者： Singgih, Ivan Kristianto Yu, Onyu Kim, Byung-In Koo, Jeongin Lee, Seungdoe Pohang Univ Sci & Technol Dept Ind & Management Engn Pohang South Korea Korea Inst Ind Technol Res Inst Sustainable Mfg Syst Cheonan South Korea Hankuk Met Co Ltd Gyeongju South Korea

In a factory of automobile component primer painting, various automobile parts are attached to overhead hangers in a conveyor line and undergo a series of coating processes. Thereafter, the components are wrapped at a packaging station. The packaging process should be fully balanced by an appropriate sequence of components to prevent the bottleneck effect because each component requires different packaging times and materials. An overhead hanger has a capacity limit and can hold varying numbers of components depending on the component type. Capacity loss can occur if the hanger capacity is not fully utilized. To increase hanger utilization, companies sometimes mix two or more component types on the same hangers, and these hangers are called mixed hangers. However, mixed hangers generally cause heavy workload because different items require additional setup times during hanging and packing processes. Hence, having many mixed hangers is not recommended. A good production schedule requires a small number of mixed hangers and maximizes hanger utilization and packaging workload balance. We show that the scheduling problem is NP-hard and develop a mathematical programming model and efficient solution approaches for the problem. When applying the methods to solve real problems, we also use an initial solution-generating method that minimizes the mixing cost, set a rule for hanging the items on hangers considering eligibility constraint, and decrease the size of tabu list in proportion to the remaining computational time for assuring intensification in the final iterations of the search. Experimental results demonstrate the effectiveness of the proposed approaches.

关键词： Flow shop scheduling Automobile component primer painting mixed-integer programming Heuristic algorithms

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Hybrid simulated annealing and reduced variable neighbourhood search for an aircraft scheduling and parking problem

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INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH 2020年第9期58卷 2626-2646页

作者： Zheng, Shuang Yang, Zhen He, Zhengwen Wang, Nengmin Chu, Chengbin Yu, Haiyang Xi An Jiao Tong Univ Sch Management Xian Shaanxi Peoples R China Univ Paris Est ESIEE Paris Noisy Le Grand France China Acad Civil Aviat Sci & Technol Beijing Peoples R China

Aircraft stands and runways at airports are critical airport resources for aircraft scheduling and parking. Making use of limited apron and runway resources to improve airport efficiency is becoming increasingly important. In this paper, we study a realistic Aircraft Scheduling and Parking Problem (ASPP) with the goal of simultaneously determining the takeoff and landing time of each aircraft with consideration for wake vortex effect constraints and parking positions in the limited parking apron at a target airport. The objective of the ASPP is to minimise the total service time for aircraft. We developed a mixed-integer linear programme formulation for the ASPP. A novel improved bottom-left/right strategy is applied to construct solutions and a Hybrid Simulated Annealing and Reduced Variable Neighborhood Search (HSARVNS) is proposed to identify near-optimal solutions. Numerical experiments on randomly generated ASPP instances and on a large set of benchmarks for a reduced version of the ASPP (i.e. the classical Two-Dimensional Strip-Packing Problem (2D-SPP)) demonstrate the effectiveness and efficiency of the proposed approach. For the ASPP, HSARVNS can find optimal solutions for small instances in a fraction of a second and can find high-quality solutions for instances with up to 250 aircraft within a reasonable timeframe. For the 2D-SPP, the HSARVNS can find optimal solutions for 32 of 38 tested benchmarks within 90 s on average.

关键词： Aircraft scheduling mixed-integer programming strip-packing meta-heuristic

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