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Route, speed, and bunkering optimization for LNG-fueled tramp ship with alternative bunkering ports

OCEAN ENGINEERING 2024年 305卷

作者： He, Ping Jin, Jian Gang Pan, Wei Chen, Jianghang Shanghai Jiao Tong Univ Sch Ocean & Civil Engn Shanghai 200240 Peoples R China Shanghai Jiao Tong Univ MOE Key Lab Marine Intelligent Equipment & Syst Shanghai 200240 Peoples R China Shanghai Jiao Tong Univ State Key Lab Ocean Engn Shanghai 200240 Peoples R China Liaoning Univ Int Business & Econ Inst Big Data Res Dalian 116052 Peoples R China Xian Jiaotong Liverpool Univ Int Business Sch Suzhou 215123 Peoples R China

To reduce emissions, shipping companies are deploying eco-friendly ships, like those powered by LNG or methanol. Unlike traditional fuels, LNG bunkering is available at a limited number of ports. At the same time, tramp or bulk ships have fewer ports of call on their shipping lines, which may necessitate LNGfueled ships sailing to alternative bunkering ports for refueling. The selection of bunkering ports impacts the operating costs of shipping lines due to differences in fuel prices and geographical locations. Moreover, it must factor in ship speed limits to meet loading and unloading schedules. To optimize the shipping route, speeds, and bunkering plan for LNG-fueled tramp ships, we develop an arc-based mixed-integer linear programming model with the objective of minimizing total operation costs. Subsequently, we propose a leg -based formulation based on the predetermined port call orders. Finally, case studies are conducted to demonstrate the effectiveness and efficiency of the models. Experimental results indicate that the bunkering mode with alternative bunkering ports effectively reduces total operating costs without altering the total voyage time, particularly with substantial differences in fuel prices between ports.

关键词： LNG-fueled tramp ship Alternative bunkering ports Optimization of shipping line mixed-integer programming

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New algorithm for the flexibility index problem of quadratic systems

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AICHE JOURNAL 2018年第7期64卷 2486-2499页

作者： Jiang, Hao Chen, Bingzhen Grossmann, Ignacio E. Tsinghua Univ Inst Proc Syst Engn Dept Chem Engn Beijing 100084 Peoples R China Carnegie Mellon Univ Dept Chem Engn Ctr Adv Proc Decis Making Pittsburgh PA 15213 USA

A new flexibility index algorithm for systems under uncertainty and represented by quadratic inequalities is presented. Inspired by the outer-approximation algorithm for convex mixed-integer nonlinear programming, a similar iterative strategy is developed. The subproblem, which is a nonlinear program, is constructed by fixing the vertex directions since this class of systems is proved to have a vertex solution if the entries on the diagonal of the Hessian matrix are non-negative. By overestimating the nonlinear constraints, a linear min-max problem is formulated. By dualizing the inner maximization problem, and introducing new variables and constraints, the master problem is reformulated as a mixed-integer linear program. By iteratively solving the subproblem and master problem, the algorithm can be guaranteed to converge to the flexibility index. Numerical examples including a heat exchanger network, a process network, and a unit commitment problem are presented to illustrate the computational efficiency of the algorithm. (c) 2018 American Institute of Chemical Engineers AIChE J, 64: 2486-2499, 2018

关键词： flexibility index mixed-integer programming quadratic systems overestimation

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AN OPTIMAL PATH PLANNING PROBLEM FOR HETEROGENEOUS MULTI-VEHICLE SYSTEMS

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INTERNATIONAL JOURNAL OF APPLIED MATHEMATICS AND COMPUTER SCIENCE 2016年第2期26卷 297-308页

作者： Klauco, Martin Blazek, Slavomir Kvasnica, Michal Slovak Univ Technol Bratislava Inst Informat Engn Automat & Math Fac Chem & Food Technol Radlinskeho 9 Bratislava Slovakia Slovak Univ Technol Bratislava Inst Informat Engn Automat & Math Radlinskeho 9 Bratislava Slovakia

A path planning problem for a heterogeneous vehicle is considered. Such a vehicle consists of two parts which have the ability to move individually, but one of them has a shorter range and is therefore required to keep in a close distance to the main vehicle. The objective is to devise an optimal path of minimal length under the condition that at least one part of the heterogeneous system visits all desired waypoints exactly once. Two versions of the problem are considered. One assumes that the order in which the waypoints are visited is known a priori. In such a case we show that the optimal path can be found by solving a mixed-integer second-order cone problem. The second version assumes that the order in which the waypoints are visited is not known a priori, but can be optimized so as to shorten the length of the path. Two approaches to solve this problem are presented and evaluated with respect to computational complexity.

关键词： path planning multi-vehicle system mixed-integer programming

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Nurse scheduling with quick-response methods: Improving hospital performance, nurse workload, and patient experience

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EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2020年第1期283卷 390-403页

作者： Schoenfelder, Jan Bretthauer, Kurt M. Wright, P. Daniel Coe, Edwin Univ Augsburg Fac Business Adm & Econ Hlth Care Operat Hlth Informat Management D-86159 Augsburg Germany Indiana Univ Kelley Sch Business Operat & Decis Technol Dept Bloomington IN 47405 USA Villanova Univ Sch Business Management & Operat Dept Villanova PA 19085 USA St Anthony Hosp CHI Franciscan Hlth Gig Harbor WA 98332 USA

Hospitals continue to face the challenge of providing high-quality patient care in an environment of rising healthcare costs. In response, a great deal of attention has been given to advance planning decisions such as nurse staffing, bed mix, scheduling, and patient flow. However, less attention has been given to incorporating quick-response methods in the nurse scheduling process by both anticipating and responding to patient demand fluctuations. Therefore, in this paper, we present a model that incorporates two classes of quick-response decisions in hospitals' nurse scheduling: (i) adjustments to the unit assignments of cross-trained float nurses and (ii) transfers of patients between units and off-unit admissions. Analyzing three hospitals that are subject to different regulations with respect to patient-to-nurse ratios allows us to draw conclusions on how these hotly debated ratios impact hospital performance, nurse workload, and patient experience. We find that quick-response via cross-trained nurses may lead to higher total costs in settings where an upper limit on patient-to-nurse ratios is enforced. This result has significant managerial and political relevance in locations such as California. Another takeaway is that only a small number of patient transfers or off-unit admissions provides close to the full potential benefit, thus minimizing the negative impact on patient satisfaction and quality of care. Moreover, our proposed scheduling approach reduces the number of undesired assigned shifts. Finally, bed and nurse capacity utilization are shown to be important considerations when determining how and whether to use quick-response methods. (C) 2019 Elsevier B.V. All rights reserved.

关键词： OR in health services Nurse scheduling Quick-response methods Flexibility mixed-integer programming

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Partial objective inequalities for the multi-item capacitated lot-sizing problem

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COMPUTERS & OPERATIONS RESEARCH 2018年 91卷 132-144页

作者： Buyuktahtakin, I. Esra Smith, J. Cole Hartman, Joseph C. New Jersey Inst Technol Dept Mech & Ind Engn Newark NJ 07102 USA Clemson Univ Dept Ind Engn Clemson SC 29631 USA Univ Massachusetts Lowell Coll Engn Lowell MA USA

In this paper, we study a mixed-integer programming model of the single-level multi-item capacitated lot-sizing problem (MCLSP), which incorporates shared capacity on the production of items for each period throughout a planning horizon. We derive valid bounds on the partial objective function of the MCLSP formulation by solving the first t periods of the problem over a subset of all items, using dynamic programming and integer programming techniques. We also develop algorithms for strengthening these valid inequalities by back-lifting techniques. These inequalities can be utilized within a cutting-plane algorithm, in which we perturb the partial objective function coefficients to identify violated inequalities to the MCLSP polytope. Our computational results show that the envelope inequalities are very effective for the MCLSP instances with different capacity and cost characteristics, when compared to the (l, S) inequalities. (C) 2017 Elsevier Ltd. All rights reserved.

关键词： mixed-integer programming Dynamic programming Cutting planes Valid inequalities Partial objective cuts (l, S) inequalities Polyhedral study Branch-and-cut Multi-item Capacitated lot-sizing Production planning

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Rescue therapy planning based on HIV genotyping testing

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CHEMICAL ENGINEERING SCIENCE 2013年 93卷 445-466页

作者： Joly, Marcel Odloak, Darci Univ Sao Paulo Proc Control & Simulat Lab Dept Chem Engn BR-05508900 Sao Paulo Brazil

Focusing on the HIV-1 subtype B epidemic, the most frequent HIV variant in Brazil, we extend our work on HIV modeling and propose a practical decision-making framework for the design of individualized HIV-1 drug chemotherapy strategies relying on patient-specific genotyping test data. The methodology is applied to 9 real-world problem instances regarding a set of 15 antiretroviral drugs and a set of 62 amino acid mutations along 45 positions of the HIV-1 pol gene. Optimized strategies are compared with current guidelines from the Brazilian standard HIV/AIDS treatment protocol. Computational results show that distinct optimal treatment strategies are produced for different patients and we conclude that relevant opportunities are to be promptly exploited on an individual basis through a better management of HIV-1 mutations in the long-term, which can be achieved by frequently changing the HAART scheme over time in response to and in anticipation of the emergence of drug-resistant strains. (C) 2013 Elsevier Ltd. All rights reserved.

关键词： Biomedical engineering Pharmacogenomics Virus-like particle Mathematical modeling mixed-integer programming Optimization

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Permutation flow shop scheduling with multiple lines and demand plans using reinforcement learning

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EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2022年第1期299卷 75-86页

作者： Brammer, Janis Lutz, Bernhard Neumann, Dirk Volkswagen AG Berliner Ring 2 D-38440 Wolfsburg Germany Univ Freiburg Rempartstr 16 D-79098 Freiburg Germany

Existing studies on the permutation flow shop problem (PFSP) commonly assume that jobs are produced on a single line. However, manufacturers may speed up their production by employing multiple lines, where each line produces sub-parts of the final product;which must be assembled by a synchronization machine. This study presents a novel reinforcement learning (RL) approach for the PFSP with multiple lines and demand plans. Our approach differs from existing RL-based scheduling methods as we train the policy to directly generate the sequence in an iterative way, where actions denote the job type to be sequenced next. During cutoff time, we follow a multistart approach that generates sequences with the trained policy, which are subsequently optimized by local search. Our numerical evaluation based on 1050 problem instances with up to three production lines shows that our approach outperforms existing methods on the multi-line problems for short cutoff times, while there is a tie with existing methods for medium and long cutoff times. A further analysis suggests that our approach can also be applied to problems with imbalanced demand plans. (c) 2021 Elsevier B.V. All rights reserved.

关键词： Scheduling Permutation flow shop problem Reinforcement learning mixed-integer programming Constraint programming

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Maximizing a submodular function by integer programming: Polyhedral results for the quadratic case

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EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 1996年第1期94卷 154-166页

作者： Lee, H Nemhauser, GL Wang, YH GEORGIA INST TECHNOL SCH IND & SYST ENGNATLANTAGA 30332

We give a new mixed integer programming (MIP) formulation for the quadratic cost partition problem that is derived from a MIP formulation for maximizing a submodular function, Several classes of valid inequalities for the convex hull of the feasible solutions are derived using the valid inequalities for the node packing polyhedron. Facet defining conditions and separation algorithms are discussed and computational results are reported.

关键词： quadratic cost partition submodular function mixed-integer programming

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A pattern based, robust approach to cyclic master surgery scheduling

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JOURNAL OF SCHEDULING 2012年第5期15卷 553-563页

作者： Mannino, Carlo Nilssen, Eivind J. Nordlander, Tomas Eric Univ Roma La Sapienza Dept Comp & Syst Sci Rome Italy SINTEF ICT Dept Appl Math N-0314 Oslo Norway

The Master Surgery Scheduling problem consists of finding a suitable allocation of operating resources to surgical groups. A myriad of variants of the problem has been addressed in literature. Here we focus on two major variants, arising during a cooperation with Sykehuset Asker og B'rum HF, a large hospital in the city of Oslo. The first variant asks for balancing patient queue lengths among different specialties, whereas the second for minimizing resort to overtime. To cope with these problems we introduce a new mixed integer linear formulation and show its beneficial properties. Both problems require the estimation of demand levels. As such estimation is affected by uncertainty, we also develop a light robustness approach to the second variant. Finally we present computational results on a number of real-world instances provided by our reference hospital.

关键词： Health-care optimization Master surgery scheduling Robust optimization mixed-integer programming

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Short-term scheduling of an open-pit mine with multiple objectives

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ENGINEERING OPTIMIZATION 2017年第5期49卷 777-795页

作者： Blom, Michelle Pearce, Adrian R. Stuckey, Peter J. Univ Melbourne Dept Comp & Informat Syst Parkville Vic Australia

This article presents a novel algorithm for the generation of multiple shortterm production schedules for an open-pit mine, in which several objectives, of varying priority, characterize the quality of each solution. A shortterm schedule selects regions of a mine site, known as 'blocks', to be extracted in each week of a planning horizon (typically spanning 13 weeks). Existing tools for constructing these schedules use greedy heuristics, with little optimization. To construct a single schedule in which infrastructure is sufficiently utilized, with production grades consistently close to a desired target, a planner must often run these heuristics many times, adjusting parameters after each iteration. A planner's intuition and experience can evaluate the relative quality and mineability of different schedules in a way that is difficult to automate. Of interest to a short-term planner is the generation of multiple schedules, extracting available ore and waste in varying sequences, which can then be manually compared. This article presents a tool in which multiple, diverse, short-term schedules are constructed, meeting a range of common objectives without the need for iterative parameter adjustment.

关键词： short-term open-pit mine production scheduling multi-objective optimization mixed-integer programming decision support

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