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A branch-and-bound algorithm for two-machine flow-shop scheduling problems with batch delivery costs

International Journal of Systems Science: Operations and Logistics 2014年第2期1卷 94-104页

作者： Mazdeh, Mohammad Mahdavi Rostami, Mohammad Department of Industrial Engineering Iran University of Science & Technology Tehran Iran

Manufacturers often dispatch jobs in batches to reduce delivery costs. However, this technique can have a negative effect on other scheduling-related objective functions such as minimising maximum tardiness. This paper aims to minimise the maximum tardiness and the sum of delivery costs of a two-machine flow-shop problem in a batch delivery system. It is proven in the literature that this problem is NP-complete. We present a mixed integer linear programming (MILP) model to solve the problem. As this is an MILP model, the commercial solver (the GAMS software using CPLEX solver) is not guaranteed to find the optimal solution for large-size problems at a logical CPU run time. Therefore, a branch-and-bound (B&B) algorithm is proposed for obtaining the optimum solution. Additionally, an upper bound (UB) heuristic with a quick processing time is presented. These methods are evaluated using randomly generated instances and the results indicate the efficiency of the B&B and UB heuristic algorithms. © 2014, © 2014 Taylor & Francis.

关键词： batched delivery system branch-and-bound algorithm maximum tardiness mixed integer linear programming two-machine flow-shop scheduling

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Optimising nurse schedules at a community health centre

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OPERATIONS RESEARCH FOR HEALTH CARE 2021年 30卷 100308-100308页

作者： Zimmerman, Samantha L. Bi, Alan Dallow, Trevor Rutherford, Alexander R. Stephen, Tamon Bye, Cameron Hall, David Day, Andrew Latham, Nicole Vasarhelyi, Krisztina Simon Fraser Univ Dept Math 8888 Univ Dr Burnaby BC V5A 1S6 Canada Simon Fraser Univ SFU Big Data 8888 Univ Dr Burnaby BC V5A 1S6 Canada Simon Fraser Univ Fac Hlth Sci 8888 Univ Dr Burnaby BC V5A 1S6 Canada Vancouver Coastal Hlth 520 W 6th Ave Vancouver BC V5Z 4H5 Canada

We present a new scheduling approach to improve access to care at an inner-city community health centre in Vancouver, Canada, serving marginalised clients with complex biopsychosocial needs. In order to meet the specific care needs of clients, the centre provides a range of services on a booked and walk-in basis, and it is important that clients are seen in a timely manner. To align schedules with client demand, we developed a schedule optimisation model that maximises time nurses spend with clients. This new objective function allows for a simple mixed integer linear programming structure that directly incorporates carryover demand. Client-centred key performance indicators were evaluated using a discrete event simulation model. Optimisation aligns schedules to demand, leading to fewer clients who leave without being seen due to an extended wait. This increases the number of clients receiving care by up to 9 per week, without compromising wait times. Furthermore, our approach addresses service delivery concerns, including baseline nurse coverage for triage and weekly variability in total nurse hours. Strategically aligning nurse shifts to demand is an effective approach to better meet client needs without increasing total nurse staffing levels in a community health centre context. (C) 2021 Elsevier Ltd. All rights reserved.

关键词： Nurse schedule optimisation Primary health care Access to care Health equity mixed integer linear programming Discrete event simulation

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On the Performance of the Subtour Elimination Constraints Approach for the p-Regions Problem: A Computational Study

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GEOGRAPHICAL ANALYSIS 2018年第1期50卷 32-52页

作者： Carlos Duque, Juan Velez-Gallego, Mario C. Catalina Echeverri, Laura Univ EAFIT Sch Econ & Finance RiSE Medellin Colombia Univ EAFIT Dept Prod Engn Medellin Colombia

The p-regions is a mixed integer programming (MIP) model for the exhaustive clustering of a set of n geographic areas into p spatially contiguous regions while minimizing measures of intraregional heterogeneity. This is an NP-hard problem that requires a constant research of strategies to increase the size of instances that can be solved using exact optimization techniques. In this article, we explore the benefits of an iterative process that begins by solving the relaxed version of the p-regions that removes the constraints that guarantee the spatial contiguity of the regions. Then, additional constraints are incorporated iteratively to solve spatial discontinuities in the regions. In particular we explore the relationship between the level of spatial autocorrelation of the aggregation variable and the benefits obtained from this iterative process. The results show that high levels of spatial autocorrelation reduce computational times because the spatial patterns tend to create spatially contiguous regions. However, we found that the greatest benefits are obtained in two situations: (1) when n/p >= 3;and (2) when the parameter p is close to the number of clusters in the spatial pattern of the aggregation variable.

关键词： GEOGRAPHY -- Mathematical models CONSTRAINT algorithms mixed integer linear programming AUTOCORRELATION (Statistics) AGGREGATION (Statistics) ITERATIVE methods (Mathematics)

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Multi-objective optimization in real-time operation of rainwater harvesting systems

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EURO JOURNAL ON DECISION PROCESSES 2023年 11卷

作者： Zhen, Yi Smith-Miles, Kate Fletcher, Tim D. Burns, Matthew J. Coleman, Rhys A. Univ Melbourne Sch Math & Stat Parkville Vic 3010 Australia Univ Melbourne Sch Ecosyst & Forest Sci Parkville Vic 3010 Australia Melbourne Water 990 La Trobe St Docklands Vic 3008 Australia

Increased population growth and urbanization have brought critical challenges to urban water systems, including water scarcity and environmental degradation. To address the problems, real-time controlled rainwater storages are now being used to reduce flooding by intercepting rainfall, while also providing an alternate water supply and actively restoring baseflow to improve biodiversity outcomes. These benefits can be enhanced when the storages are managed as an optimized network. This paper proposes a multi-objective-optimization-based strategy utilizing mixed integer linear programming and compromise programming to control a network of rainwater storages. The proposed strategy is observed to substantially reduce storage overflow, improve stream baseflow, and fulfill most of the domestic non-potable water demand. It shows a clear advantage over the NSGA II-based strategy, indicating the effectiveness of mathematical programming with scalarization techniques in solving multi-objective problems.

关键词： multi-objective optimization water resource management receding horizon approach rainwater harvesting system mixed integer linear programming compromise programming

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***-A model generator for linear and mixed-integer linear optimisation of energy systems

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SOFTWARE IMPACTS 2020年 6卷

作者： Krien, Uwe Schoenfeldt, Patrik Launer, Jann Hilpert, Simon Kaldemeyer, Cord Plessmann, Guido Univ Bremen Dept Resilient Energy Syst Enrique Schmidt Str 7 D-28359 Bremen Germany DLR Inst Networked Energy Syst Carl von Ossietzky Str 15 D-26129 Oldenburg Germany Reiner Lemoine Inst Rudower Chaussee 12 D-12489 Berlin Germany Europa Univ Flensburg Campus 1 D-24943 Flensburg Germany Zentrum Nachhaltige Energiesyst Munketoft 3b-119 D-24937 Flensburg Germany Flensburg Univ Appl Sci Kanzleistr 91-93 D-24943 Flensburg Germany

Energy system modelling is of high importance to investigate different scenarios in their technical, economical and environmental feasibility. The interplay of different technologies and energy flows in respective models can be represented as directed graphs in a generic but comprehensible formalism. However, additional effort is needed to create specific models and to derive an optimal sizing or operation of components. To tackle this problem, *** facilitates the formulation of (mixed-integer) linear programs from a generic object-oriented structure. Its structure allows to create models on different levels of detail by means of predefined components and an optional formulation of additional expressions and constraints. With its open and documented code base, extensive collection of examples and an active community it is useful across many levels, from simple applications to advanced modelling.

关键词： Energy system modelling Dispatch optimisation Optimal sizing mixed integer linear programming

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Multi-skill resource-constrained project scheduling problem considering overlapping: fuzzy multi-objective programming approach to a case study

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INTERNATIONAL JOURNAL OF CONSTRUCTION MANAGEMENT 2024年第8期24卷 820-833页

作者： Zarei, Fateme Arashpour, Mehrdad Mirnezami, Seyed-Ali Shahabi-Shahamiri, Reza Ghasemi, Mohammad Tech & Vocat Univ TVU Maeda Girls Coll Dept Architecture Gorgan Iran Monash Univ Dept Civil Engn Melbourne Australia Shahed Univ Fac Engn Dept Ind Engn Tehran Iran Univ Tehran Coll Engn Dept Ind Engn Tehran Iran

Resource-constrained project scheduling problem (RCPSP) is a broadly researched issue in the literature. The purpose of the classic form of the problem is scheduling a set of activities considering resource and precedence constraints for minimizing the project completion time. Companies mostly deal with the issue of properly assigning multi-skilled workforces and maintaining the needed skill levels while implementing projects. In this study, a novel MILP model with three objectives is presented to tackle multi-skill RCPSP (MS-RCPSP). This study concentrates on minimizing project makespan, minimizing resource costs as well as tardiness costs, and maximizing quality under uncertainty. However, the standard MS-RCPSP is not able to consider several practical engineering requirements owing to its narrow assumptions. Therefore, key assumptions including overlap between activities, tardiness penalties of activities and the rework duration concept for activities in this model are considered. Due to the complexity of the real world, interval valued fuzzy numbers are taken into account for some of the problem's parameters. The efficiency of the proposed mathematical framework is represented using both a real case study to construct a railway bridge with 34 activities and large-size problem instances from MMLIB (MM50 and MM100). Since this model is multi-objective, a new extended IVF-ABS approach is presented in this study. Finally, the proposed approach is compared with two methods, namely SO and ABS, from the literature.

关键词： Multi-objective multi-skill project scheduling overlapping mixed integer linear programming

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An airport gate reassignment problem with gate closures

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JOURNAL OF AIR TRANSPORT MANAGEMENT 2024年 115卷

作者： Poyraz, Dursen Deniz Azizoglu, Meral Erasmus Univ Rotterdam Sch Management NL-3062 PA Rotterdam Netherlands Middle East Tech Univ Dept Ind Engn TR-06800 Ankara Turkiye

In this study, we consider an airport gate reassignment problem where an airport has assigned gates to aircraft, but then a disruption occurs at some of the gates. After the disruption, we need to reassign the aircraft to the gates while taking into account both efficiency and stability measures. For efficiency, we want to use the gates as much as possible, considering both the number of aircraft and the number of passengers in these aircraft. For stability, we want to stick as closely as possible to the initial plan. We suggest solution procedures for finding two extreme ends of the nondominated objective vectors, all extreme supported nondominated objective vectors, and all nondominated objective vectors with respect to our efficiency and stability measures. An optimal decomposition rule is presented to simplify the complexity of the solution. Our extensive experiments have shown that our optimization procedures can handle the instances with up to 150 aircraft and 40 gates, and approximation algorithms can handle the instances with up to 200 aircraft and 40 gates.

关键词： Airport gate reassignment problem mixed integer linear programming Nondominated objective vectors

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A mathematical programming approach for procurement using activity based costing

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Journal of Business Finance and Accounting 2000年第1-2期27卷 69-98页

作者： Degraeve, Zeger Roodhooft, Filip London Business School United Kingdom Katholieke Universiteit Leuven Belgium

Activity Based Costing and Management are important topics in today's management accounting literature. While there has been much attention paid in the Activity Based Costing literature to customer profitability analysis, process improvement and product design, there has been far less notice taken of purchasing. In this paper we develop an Activity Based Costing approach for the determination of procurement strategies. Vendor selection using an Activity Based Costing approach is choosing the combination of suppliers for a given product group that minimizes the total costs associated with the purchasing strategy. To this end we develop a mathematical programming model where decisions involve the selection of vendors and the determination of order quantities. The system computes the total cost of ownership, thereby increasing the objectivity in the selection process and giving the opportunity for various kinds of sensitivity analysis.

关键词： activity based costing procurement accounting/operations research interface mixed integer linear programming

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Modeling patient preference in an operating room scheduling problem

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OPERATIONS RESEARCH FOR HEALTH CARE 2020年 25卷

作者： Ahmed, Abdulaziz Ali, Haneen Univ Minnesota Business Dept Crookston MN USA Auburn Univ Ind & Syst Engn Dept Hlth Serv Adm Program Auburn AL 36849 USA

When a patient needs plastic surgery and there are multiple available surgeons, the patient selects the surgeon based on different criteria. Accommodating patient preference while scheduling such surgeries is important as it is related to patient satisfaction. In this study, we propose a framework for integrating patient preference in an operating room (OR) scheduling problem. To model patient preference to a surgeon, we propose nine criteria: responsive and caring, reputation, professional experiences, communication skills, same ethnicity, same gender, age, same language, and online rating. Fuzzy TOPSIS (namely, Technique for Order of Preference by Similarity to Ideal Solution) is then employed to quantify patient preference to surgeons. The outcomes of fuzzy TOPSIS are then fed into a multi-objective mixed-integer linear programming (MILP) model to optimize daily surgery schedule. The proposed study is based on a real-life case study that was conducted in a plastic surgery department at a partner hospital. The computational results show that when patient preference to surgeon is considered, more than 70% of patients are assigned to their most preferred surgeons, and less than 5% are assigned to their least preferred surgeons. However, when patient preference is not considered, less than 20% of patients are assigned to most preferred surgeons, and the others are assigned to less preferred surgeons. When it comes to the total costs, the two scenarios results are similar. This concludes that the proposed framework is robust and able to increase patient satisfaction in OR scheduling without sacrificing the total OR operational costs. (C) 2020 Elsevier Ltd. All rights reserved.

关键词： Fuzzy TOPSIS Operating room scheduling Patient preference mixed integer linear programming

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A Comparative Analysis of Energy Storage and N-1 Network Security in Transmission Expansion Planning

A Comparative Analysis of Energy Storage and N-1 Network Sec...

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International Universities Power Engineering Conference

作者： E. B. Obio J. Mutale The University Of Manchester

ISBN: (纸本)9781467396578

In a restructured power system, one of the key objectives of transmission network expansion is to provide nondiscriminatory access to cheaper generation for all consumers. However, the robustness of the transmission network against all uncertainties such as credible contingencies should equally be maintained. Thus the development of effective methodologies and strategies to satisfy this objective is a major challenge faced by the transmission expansion planners in the new environment. In this paper a static transmission expansion model with energy storage is proposed. The energy storage is coordinated with transmission expansion planning in a system with base load generators and expensive peaking power plants. The energy storage is modelled to store the cheaper generation from the base load power plants at off peak periods and discharges to meet the demand at peak periods. Four distinct transmission expansion models with and without energy storage system (ESS) and N-1 network security constraint are developed for the comparative analysis. The whole problem is formulated as a mixed integer linear programming (MILP) problem with the objective of minimizing the operational cost of the generators as well as the transmission line and storage investment costs over several demand levels. The proposed methodology is demonstrated on the IEEE 24 bus reliability test system (RTS). The overall results from the model showed that energy storage benefits the system by deferring investment in transmission lines. The model also confirmed that the marginal benefit of storage diminishes as the investment in ESS increases. In addition, the economic viability of corrective planning over preventive planning of transmission network is also justified.

关键词： Comparative analysis Energy storage mixed integer linear programming N-1 network security Transmission investment Transmission expansion planning

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