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Vessel scheduling with pilotage and tugging considerations

TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW 2021年 148卷 102231-102231页

作者： Abou Kasm, Omar Diabat, Ali Bierlaire, Michel NYU Dept Civil & Urban Engn Tandon Sch Engn Brooklyn NY 11201 USA New York Univ Abu Dhabi Div Engn Abu Dhabi 129188 U Arab Emirates Ecole Polytech Fed Lausanne Sch Architecture Civil & Environm Engn Transport & Mobil Lab TRANSP OR Lausanne Switzerland

This paper considers vessel scheduling with pilotage and tugging constraints in berthing operations with channel restrictions at seaports. To our knowledge, pilotage and tugging requirements have not been simultaneously considered in the literature. This work proposes a mixed integer programming (MIP) formulation and an exact solution approach, based on constraint separation techniques, to solve the problem. The solution approach is initiated with a heuristic that runs in polynomial time. The approach then adds separation cuts to a relaxed version of the MIP formulation and updates the bounds until an optimal solution has been found. A real case and simulated realistic cases are used to compare the proposed model against the first-come first-serve (FCFS) policy that is traditionally used in vessel scheduling. The results show that significant improvements can be obtained, especially during congestion periods. Finally, a computational study demonstrates that the proposed solution approach is capable of solving real-size cases in a reasonable time.

关键词： Vessel scheduling Tug assistance Pilotage constraints Channel restrictions mixed integer programming Exact solution approach

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Deploying a shipping infrastructure to enable carbon capture and storage from Norwegian industries

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JOURNAL OF CLEANER PRODUCTION 2022年 333卷

作者： Bjerketvedt, Vegard Skonseng Tomasgard, Asgeir Roussanaly, Simon Norwegian Univ Sci & Technol NTNU Dept Ind Econ & Technol Management N-7491 Trondheim Norway SINTEF Energy Res Sem Saelandsvei 11 NO-7465 Trondheim Norway

This paper investigates the deployment over time of a shipping infrastructure to enable carbon capture and storage from Norwegian industries. In particular, optimal transport investments, routing, shipping portfolio, and transport conditions required cost-efficiently connect nine Norwegian and Swedish industrial facilities to the Northern Light Initiative are identified based on a multi-period mixed-integer model. Optimization of the shipping portfolio allows us to analyze the potential benefits of economics of scale and how sailing multi-stop routes can utilize the potential benefits. Analyses show that the transport cost can be reduced by 12% when the optimal shipping portfolio is implemented instead of operating an independent transport chain for each emission source. Shipping at 7-bar is expected to result in lower costs compared 15-bar shipping, but a significant drawback is the technological maturity of the 7-bar transport technology. The model proposes two transport chains run in parallel as cost optimal, the average transport cost of the 15-bar chain is 32.4 euro/ton, and the 7-bar has an average cost of 25.4 euro/ton. A net present value criterion is used to identify the conditions for when retrofitting of the 15-bar transport chain is economically sound. Break-even is achieved when the ship's re-sale price is 60% of the purchase price, and the cost of retrofitting a 15-bar conditioning plant to a 7-bar is 40% of the investment cost. While retrofitting may be an attractive solution, the decisions lead to a less robust shipping portfolio, and the retrofitting of a fully operating carbon capture and storage value chain is regarded as unlikely.

关键词： Carbon capture and storage CO 2 transport CO 2 shipping Norwegian industry mixed integer programming CO 2-Shipping

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Robustness of solutions to critical node detection problems with imperfect data: a computational study

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OPTIMIZATION METHODS & SOFTWARE 2017年第2期32卷 250-273页

作者： Gillen, Colin P. Veremyev, Alexander Prokopyev, Oleg A. Pasiliao, Eduardo L. Univ Pittsburgh Ind Engn 1048 Benedum Hall Pittsburgh PA 15261 USA Univ Florida Ind & Syst Engn 303 Weil Hall Gainesville FL 32611 USA US Air Force Munit Directorate Res Lab Bldg 13 Eglin AFB FL 32542 USA

A class of critical node detection problems based upon the metric of communication efficiency is considered. While both exact integer programming and heuristic centrality-based methods exist for the solution of these problems, previous work has been mostly focused on the case where perfect information about the network is available. In this paper we suppose that some level of misinformation about nodes or edges has been inflicted on the observer's perception of the network, that is, there are hidden elements or fake additional elements. An extensive computational study is conducted to ascertain whether the exact integer-programming-based solutions perform better under imperfect information than heuristic methods. For large networks, exact methods cannot produce a solution in a reasonable amount of time, hence an approximation of the exact method is also considered for such instances. The obtained approximate solutions are again compared to centrality-based heuristics under the presence of imperfect data.

关键词： critical node detection distance-based metrics graph efficiency network interdiction mixed integer programming robustness sensitivity

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A hybrid modified-NSGA-II VNS algorithm for the Multi-Objective Critical Disruption Path Problem

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COMPUTERS & OPERATIONS RESEARCH 2023年第1期160卷

作者： Granata, Donatella Sgalambro, Antonino Univ Sheffield Management Sch Conduit Rd Sheffield S10 1FL England Natl Res Council Italy Ist Applicaz Calcolo Mauro Picone Via Taurini 19 I-00185 Rome Italy Univ Parma Dipartimento Sci Matemat Fis & Informat Plesso Plesso Matemat Parco Area Sci 53 A I-43124 Parma Italy

This paper considers a Multiple Objective variant of the Critical Disruption Path problem to extend its suitability in a range of security operations relying on path-based network interdiction, including flight pattern optimisation for surveillance. Given a pair of nodes s and t from the network to be monitored, the problem seeks for loopless s - t paths such that, within the induced subgraph obtained via deletion of the path, the size of the largest connected component is minimised, the number of connected components is maximised, while concurrently reducing as much as possible the cost of such disruption path. These three objectives are possibly in conflict with each other, and the scope of this work is to allow for an efficient and insightful approximation of the Pareto front, looking for a trade-off between costs and effectiveness to secure the most convenient paths for security and surveillance operations. We first introduce and formulate the Multi-Objective Critical Disruption Path Problem (Multi-Objs-CDP) as a mixed integer programming formulation (MO-CDP), then we propose an original evolutionary metaheuristic algorithm hybridising modified-NSGA-II and VNS for finding an approximation of the Pareto front, as well as a procedure securing the efficient generation of a high quality pool of initial solutions. The experimental performance of the proposed algorithm, as compared with a variety of competing approaches, proves to be fully satisfactory in terms of time efficiency and quality of the solutions obtained on a set of medium to large benchmark instances.

关键词： Networks Critical disruption path mixed integer programming Multiple objective optimisation Metaheuristics

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A Scalable Lower Bound for the Worst-Case Relay Attack Problem on the Transmission Grid

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INFORMS JOURNAL ON COMPUTING 2022年第4期34卷 2296-2312页

作者： Johnson, Emma S. Dey, Santanu Subhas Georgia Inst Technol H Milton Stewart Sch Ind & Syst Engn Atlanta GA 30332 USA Sandia Natl Labs Albuquerque NM 87185 USA

We consider a bilevel attacker-defender problem to find the worst-case attack on the relays that control transmission grid components. The attacker infiltrates some number of relays and renders all of the components connected to them inoperable with the goal of maximizing load shed. The defender responds by minimizing the resulting load shed, redispatching using a DC optimal power flow (DCOPF) problem on the remaining network. Though worst-case interdiction problems on the transmission grid have been studied for years, there remains a need for exact and scalable methods. Methods based on using duality on the inner problem rely on the bounds of the dual variables of the defender problem in order to reformulate the bilevel problem as a mixed integer linear problem. Valid dual bounds tend to be large, resulting in weak linear programming relaxations and, hence, making the problem more difficult to solve at scale. Often smaller heuristic bounds are used, resulting in a lower bound. In this work, we also consider a lower bound, but instead of bounding the dual variables, we drop the constraints corresponding to Ohm's law, relaxing DCOPF to capacitated network flow. We present theoretical results showing that, for uncongested networks, approximating DCOPF with network flow yields the same set of injections and, thus, the same load shed, which suggests that this restriction likely gives a high-quality lower bound in the uncongested case. Furthermore, we show that, in the network flow relaxation of the defender problem, the duals are bounded by one, so we can solve our restriction exactly. Finally, because the big-M values in the linearization are equal to one and network flow has a well-known structure, we see empirically that this formulation scales well computationally with increased network size. Through empirical experiments on 16 networks with up to 6,468 buses, we find that this bound is almost always as tight as we can get from guessing the dual bounds even for cong

关键词： bilevel programming interdiction mixed integer programming

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Stockyard storage space allocation in large iron ore terminals

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COMPUTERS & INDUSTRIAL ENGINEERING 2022年 164卷

作者： Tang, Xinyu Jin, Jian Gang Shi, Xiaoning Shanghai Jiao Tong Univ Sch Naval Architecture Ocean & Civil Engn Shanghai 200240 Peoples R China Shanghai Jiao Tong Univ State Key Lab Ocean Engn Shanghai 200240 Peoples R China German Aerosp Ctr DLR Rudower Ch 7 D-12489 Berlin Germany Univ Hamburg VMP5 D-20146 Hamburg Germany

Due to the increasing large demand of iron ore, large iron ore terminals are becoming critical nodes in the international shipping network. As the buffer area for temporary storage of iron ore, stockyards of iron ore terminals often emerge as the bottlenecks in the entire transportation process. Traditional experience-based operation strategy for iron ore terminals is insufficient to handle mega-size terminals and more complicated operations, such as ore-mixing. As compared to container terminals, relatively little attention has been paid to the stockyard space management of dry bulk terminals. It is of great necessity to improve the stockyard operations of iron ore terminals via operations research and optimization techniques. In this paper, we investigate the stockyard storage space allocation problem arising from large iron ore terminals with particular consideration of the ore-mixing operations. We propose a flexible and accurate modeling approach for the storage space of the iron ore terminal stockyard, and develop a mixed integer linear programming model with the objective of minimizing total travel distance of all the incoming iron ores. A heuristic approach based on genetic algorithm is designed to obtain near-optimal solutions in an efficient way. Computational experiments based on real-world iron ore terminals are conducted, and the results show satisfactory performance of the heuristic algorithm both in efficiency and effectiveness.

关键词： Storage space allocation Iron ore terminal Ore-mixing operation mixed integer programming

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Exact and heuristic approaches to reschedule helicopter flights for personnel transportation in the oil industry

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TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW 2021年 151卷 102322-102322页

作者： Vieira, Thiago de la Vega, Jonathan Tavares, Roberto Munari, Pedro Morabito, Reinaldo Bastos, Yan Ribas, Paulo Cesar Fed Univ S ao Carlos Dept Prod Engn BR-13565905 Sao Carlos SP Brazil Petrobras SA Ctr Res & Dev Av Horacio Macedo 950 Rio De Janeiro RJ Brazil

This paper addresses a real-life short-term rescheduling problem of helicopter flights from one onshore airport to several maritime units in the context of the oil industry. This is a complex and challenging problem to solve because of the particular characteristics observed in practice, such as pending flights transferred from previous days with different recovering priorities, changes in flight timetables and helicopter assignments previously planned for the current day, time windows and minimum time intervals between take-offs from the airport and the maritime units, mandatory flight precedence, maximum flight delays, among many others. The problem consists of determining a daily flight reschedule that satisfies operational constraints and recovers all pending flights, while minimizing flight delays and costs related to helicopter usage and reassignments. We propose two mixed integer programming models to formulate the problem with all relevant characteristics, one based on the extension of traditional network flow models and other that relies on a novel event-based representation of the problem. Additionally, we develop an effective heuristic approach based on constructive and improvement heuristics, able to produce high-quality solutions within acceptable computational times. The results of computational experiments with real-life data provided by an oil company highlight the potential of the proposed approaches to support decision making in this context.

关键词： Aircraft recovery problem mixed integer programming Flight rescheduling problem Constructive and improvement heuristics Helicopters and flights re-assignments Oil industry

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Spatial connectivity in tree-level decision-support models using mathematical optimization and individual tree mapping

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FOREST POLICY AND ECONOMICS 2022年第0期139卷 1页

作者： Pascual, Adrian Guerra-Hernandez, Juan Univ Maryland Dept Geog Sci College Pk MD 20742 USA Univ Lisbon Forest Res Ctr Sch Agr P-1349017 Lisbon Portugal

Tree-level planning is gaining relevance supported by continuous advances in forest remote sensing methods. Spatial connectivity under spatial optimization methods applied to individual tree mapping data remains unexplored. This article presents a spatially explicit mathematical formulation that ensures the tree cuttings conforming a corridor can connect two points across a forest landscape. The created paths facilitate operational harvesting linking forest planning solutions to forest machinery operations. The model integrates production, economic and connectivity constraints using mixed integer programming as optimization method, while tree positions and attributes were mapped using airborne laser scanning. Model performance was tested towards different harvesting targets and for the assessment of trade-offs involving the connectivity of the solutions and the economic performance. The showcase area to test the model is pine forest located in Central Spain comprising more than 9000 detected trees. The results showed the mathematical formulation in the model is effective at creating paths connect proposed areas using optimized tree harvests. Global optimality was reached fast using mathematical programming for a complex and large combinatorial problem. The presented model is another step forward in the design of multi-objective tree-level planning models, enhancing the assimilation of planning solutions towards forest operations capable to maximize the use of individual tree mapping data.

关键词： mixed integer programming Tree selection Spatial optimization Forest management

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Protecting wildlife habitat in managed forest landscapes-How can network connectivity models help?

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NATURAL RESOURCE MODELING 2021年第1期34卷 e12286-e12286页

作者： Yemshanov, Denys Haight, Robert G. Rempel, Rob Liu, Ning Koch, Frank H. Canadian Forest Serv Nat Resources Canada Great Lakes Forestry Ctr 1219 Queen St East Sault Ste Marie ON P6A 2E5 Canada USDA Forest Serv Northern Res Stn St Paul MN USA Ontario Minist Nat Resources & Forests Ctr Northern Forest Ecosyst Res Thunder Bay ON Canada FERIT Environm Consulting Thunder Bay ON Canada USDA Forest Serv Southern Res Stn Eastern Forest Environm Threat Assessment Ctr Res Triangle Pk NC USA

Industrial forestry in boreal regions increases fragmentation and may decrease the viability of some wildlife populations, particularly the woodland caribou,Rangifer tarandus caribou. Caribou protection often calls for changes in forestry practices, which may increase the cost and reduce the available timber supply. We present a linear programming model that assesses the trade-off between habitat protection and harvesting objectives by combining harvest scheduling and optimal habitat connectivity problems. We formulate the habitat connectivity model as a network flow problem that maximizes the amount of habitat connected over a desired time span in a forested landscape, while the forestry objective maximizes net undiscounted revenues from timber harvest subject to even harvest flow and environmental sustainability constraints. We applied the approach to explore the trade-off between caribou habitat protection and harvesting goals in the Armstrong-Whitesand Forest, Ontario, Canada, a boreal forest area with prime caribou habitat. Our model also incorporates Dynamic Caribou Harvesting Scheduling (DCHS), a harvest policy currently in a place in Ontario that aims to balance the forest management and caribou protection goals in northern boreal regions. In our study area, the implementation of DCHS appears to have relatively minor impact on timber supply cost. By comparison, maximizing the protection of caribou habitat would lead to a noticeable increase of the mill gate timber cost by $3.3 m(-3)on average, while enabling habitat protection in an additional 5.0%-9.5% of the range area. Our model is generalizable and can be adapted for assessing habitat recovery and harvest goals in other regions. Recommendations for Resource Managers: Incorporating the concept of long-term habitat connectivity into forest planning can help reduce the negative impacts of harvest activities on caribou populations. Prioritizing habitat connectivity leads to a small increase in the overall ha

关键词： DCHS habitat protection harvest scheduling model I landscape connectivity mixed integer programming network flow model woodland caribou

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Integrated production and distribution scheduling for perishable products

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SCIENTIA IRANICA 2017年第4期24卷 2105-2118页

作者： Marandi, F. Zegordi, S. H. Tarbiat Modares Univ Dept Ind Engn Tehran Iran

This study is concerned with how the quality of perishable products can be improved by shortening the time interval between production and distribution. Since special types of food, such as dairy products, decay fast, the Integration of Production and Distribution Scheduling (IPDS), is investigated. This article deals with a variation of IPDS that contains a short shelf life product;hence, there is no inventory of the product in the process. Once a specific amount of the product is produced, it must be transported with the least transportation time directly to various customer positions within its limited lifespans to minimize the delivery and tardy costs required to complete producing and distributing of the product to satisfy the demand of customers within the limited deadline. After developing a mixed-integer nonlinear programming model of the problem, because it is NP-hard, an Improved Particle Swarm Optimization (IPSO) is proposed. IPSO performance is compared with commercial optimization software for small-size and moderate-size problems. For large-size ones, it is compared with the genetic algorithm existing in the literature. Computational experiments show the efficiency and effectiveness of the proposed IPSO in terms of both the quality of the solution and the time of achieving the best solution. (C) 2017 Sharif University of Technology. All rights reserved.

关键词： Production and distribution Permutation flow shop scheduling Vehicle routing problem Integration mixed integer programming Particle swarm optimization

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