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Optimizing the master surgery schedule in a private hospital

OPERATIONS RESEARCH FOR HEALTH CARE 2019年 20卷 11-24页

作者： Marques, Ines Captivo, M. Eugenia Barros, Nara Univ Lisbon Ctr Management Studies Inst Super Tecn Ave Rovisco Pais P-1049001 Lisbon Portugal Univ Lisbon Fac Ciencias Ctr Matemat Aplicacoes Fundamentais & Invest Oper P-1749016 Lisbon Portugal Univ Lisbon Fac Ciencias Dept Estat & Invest Operac P-1749016 Lisbon Portugal

This paper proposes a new mixed-integer linear programming model to build cyclic master surgery schedules (MSSs) for a case study of a medium-sized Portuguese private hospital. The problem integrates tactical and strategical decisions of operating room (OR) planning and scheduling. OR time blocks are assigned to surgical services and to individual surgeons. A target OR time per surgical specialty is not given as it is often the case of other studies in the literature. The model aims to: level the workload at downstream departments (hospitalization units);avoid sharing OR time among different surgical specialties;allocate OR time blocks to the surgical specialty with the highest number of surgeons available;renew the MSS based on recent demand for surgeries. This approach allows the surgical suite to be more efficiently managed, while increasing the sense of fairness among surgeons and facilitating the negotiation for OR time. Moreover, this automated system releases the surgical suite manager to more added value tasks. (C) 2018 Elsevier Ltd. All rights reserved.

关键词： OR in health services Operating room planning Master surgery schedule mixed-integer linear programming

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Security Constrained Unit Commitment with Corrective Transmission Switching 51

Security Constrained Unit Commitment with Corrective Transmi...

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51st North American Power Symposium (NAPS)

作者： Ramesh, Anm Venkatesh Li, Xingpeng Univ Houston Dept Elect & Comp Engn Houston TX 77004 USA

ISBN: (纸本)9781728104072

Traditionally, power system operations use a static network to deliver power and meet demand optimally. Network topology reconfiguration through transmission switching (TS) has gained significant interest recently to reduce the operational cost of power system operations. However, implementation of TS also causes large disturbance in the network and as a result the use of corrective transmission switching (CTS) in response to power system contingencies is currently being researched extensively. This paper emphasizes the importance of CTS to accomplish flexible transmission in N-1 security-constrained unit commitment (SCUC) model. An N-1 SCUC mathematical model implementing a dynamic network in the post-contingency scenario is proposed as opposed to current industry practices of static network in shortterm operations. The proposed model is tested and validated on the IEEE 24-bus system. The proposed model results in cost-effective implementation and leads to overall reduced cost, and congestion reduction in the post-contingency scenario.

关键词： Corrective transmission switching Flexible transmission mixed-integer linear programming Post-contingency congestion relief Security-constrained unit commitment Topology control

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On the equal substitution of MILP unit commitment subproblems with dynamic programming 16

On the equal substitution of MILP unit commitment subproblem...

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16th International Conference on the European Energy Market (EEM)

作者： Schwaeppe, Henrik Nobis, Moritz Mueller, Christoph Rhein Westfal TH Aachen Inst High Voltage Technol Aachen Germany

ISBN: (纸本)9781728112572

By splitting unit commitment into a coupling problem and individual unit commitment subproblems, Lagrangian relaxation is very effective in decreasing the solving time of large scale problems. Consequently, unit commitment subproblems should be solved equally fast. If they have been originally formulated in mixed-integer linear programming, performance advantages can be expected by replacing it with dynamic programming. However, it has not been reported whether a one-to-one reformulation is feasible. We suggest approaches to choose states for dynamic programming that replicate equal solutions as well as measures to reduce memory requirements. Results of the two subproblem models differ only fractionally and for explicable reasons. Subproblem computation time has been reduced by up to 100 times at modest memory requirements.

关键词： Unit commitment dynamic programming mixed-integer linear programming Lagrangian relaxation

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A Constraint programming Approach to Electric Vehicle Routing with Time Windows 1

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16th International Conference on the Integration of Constraint programming, Artificial Intelligence, and Operations Research (CPAIOR)

作者： Booth, Kyle E. C. Beck, J. Christopher Univ Toronto Dept Mech & Ind Engn Toronto ON M5S 3G8 Canada

ISBN: (数字)9783030192129

ISBN: (纸本)9783030192129;9783030192112

The Electric Vehicle Routing Problem with Time Windows (EVRPTW) extends traditional vehicle routing to address the recent development of electric vehicles (EVs). In addition to traditional VRP problem components, the problem includes consideration of vehicle battery levels, limited vehicle range due to battery capacity, and the presence of vehicle recharging stations. The problem is related to others in emissions-conscious routing such as the Green Vehicle Routing Problem (GVRP). We propose the first constraint programming (CP) approaches for modeling and solving the EVRPTW and compare them to an existing mixed-integer linear program (MILP). Our initial CP model follows the alternative resource approach previously applied to routing problems, while our second CP model utilizes a single resource transformation. Experimental results on various objectives demonstrate the superiority of the single resource transformation over the alternative resource model, for all problem classes, and over MILP, for the majority of medium-to-large problem classes. We also present a hybrid MILP-CP approach that outperforms the other techniques for distance minimization problems over long scheduling horizons, a class that CP struggles with on its own.

关键词： Electric Vehicle Routing Green Vehicle Routing Constraint programming mixed-integer linear programming Optimization

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A bi-level programming approach to locate capacitated electric vehicle charging stations 6

A bi-level programming approach to locate capacitated electr...

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6th International Conference on Control, Decision and Information Technologies (CoDIT)

作者： Makhlouf, Walid Kchaou-Boujelben, Mouna Gicquel, Celine Univ Paris Sud Lab Rech Informat Orsay France United Arab Emirates Univ Coll Business & Econ Al Ain U Arab Emirates

ISBN: (纸本)9781728105215

We consider the design of a charging infrastructure based on fast-charging capacitated stations to enable electric vehicles to carry out long-distance trips. We focus on taking into account the impact of the non-system-optimal drivers' behavior on the station capacity consumption in the modeling of the facility location problem. This leads to the formulation of a bi-level optimization model. In this bi-level program, the upper level represents the station location problem faced by the charging infrastructure provider and the lower level represents the selfish behavior of EV drivers who will seek to use the charging stations opened by the infrastructure provider to carry out their trips with a minimum number of stops. We propose a solution approach based on the reformulation of the bi-level program into a mixed-integer linear program thanks to the use of the primal-dual optimality conditions of linear programming. Our preliminary computational experiments carried out on small instances show the impact on the global system performance of ignoring the selfish drivers' behavior and the potential benefit from using a bi-level programming model.

关键词： Electric vehicles facility location capacitated stations bi-level programming mixed-integer linear programming

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Modeling a Multi-Objective Vehicle Routing Problem for Monetary Operation in the Banking System 15

Modeling a Multi-Objective Vehicle Routing Problem for Monet...

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15th Iran International Industrial Engineering Conference (IIIEC)

作者： Heidari, Majid Rahbari, Misagh Mohseni, Amir Reza Islamic Azad Univ Fac Ind & Mech Engn Dept Ind Engn Qazvin Branch Qazvin Iran Kharazmi Univ Dept Ind Engn Fac Engn Tehran Iran Elm O Farhang Univ Dept Ind Engn Fac Engn Tehran Iran

ISBN: (纸本)9781728117751

One of the principal processes in the banking system is the transportation issues. The banking system networks consist of several treasuries and several branches that transfer their vehicles from the treasuries to the branches. The main features that are considered in the banking system include the monetary operation. The main activity in order to successfully process of remittance is vehicle routing so that it can perform the monetary operation in the shortest possible time with the least risk. In this research, a multi-objective model is proposed, aimed at reducing supply chain costs, reducing the delivery time and money transfers and related risk reduction. Vehicles play an effective role in the banking system, so vehicles are considered heterogeneous. The demand associated with the branch is assumed to be time-varying and deterministic. The proposed model is a mixed-integer linear program, which is a numerical example for solving and the validation study in medium size by using General Algebraic Modeling System (GAMS) software.

关键词： Vehicle Routing Problem Banking System mixed-integer linear programming Monetary Operation Supply Chain Management

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Large-scale Multi-dimensional Assignment: Problem Formulations and GPU Accelerated Solutions 22

Large-scale Multi-dimensional Assignment: Problem Formulatio...

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22nd International Conference on Information Fusion (FUSION)

作者： Reynen, Olivia Vadrevu, Samhita Nagi, Rakesh LeGrand, Keith Univ Illinois Dept Ind & Enterprise Syst Engn Urbana IL 61801 USA Sandia Natl Labs POB 5800 Albuquerque NM 87185 USA

ISBN: (纸本)9780996452786

In this paper, we present alternate integer programming formulations for the multi-dimensional assignment problem, which is typically employed for multi-sensor fusion, multi-target tracking (MTT) or data association in general. The first formulation is the Axial Multidimensional Assignment Problem with Decomposable Costs (MDADC). The decomposable costs comes from the fact that there are only pairwise costs between stages or scans of a target tracking problem or corpuses of a data association context. The difficulty with this formulation is the large number of transitivity or triangularity constraints that ensure if entity A is associated to entity B and entity B is associated with entity C, then it must also be that entity A is associated to entity C. The second formulation uses both pairs and triplets of observations, which offer more accurate representation for kinematic tracking of targets. This formulation avoids the large number of transitivity constraints but significantly increases the number of variables due to triples. Solution to large-scale problems has alluded researchers and practitioners alike. We present solution methods based on Lagrangian Relaxation and massively parallel algorithms that are implemented on Graphics Processing Units (GPUs). We test the problem formulations and solution algorithms on MTT problems. The triples formulation tends to be more accurate for tracking measures and the MDADC solver can solve much larger problems in reasonable computational time.

关键词： Multi-dimensional Assignment Data Association Multi-target tracking mixed-integer linear programming Lagrangian Relaxation GPU computing

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Model reduction by time aggregation for optimal design of energy supply systems by an MILP hierarchical branch and bound method 31

Model reduction by time aggregation for optimal design of en...

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31st International Conference on Efficiency, Cost, Optimization, Simulation, and Environmental Impact of Energy Systems (ECOS)

作者： Yokoyama, Ryohei Shinano, Yuji Wakayama, Yuki Wakui, Tetsuya Osaka Prefecture Univ Dept Mech Engn Naka Ku 1-1 Gakuen Cho Sakai Osaka 5998531 Japan Zuse Inst Berlin Dept Optimizat Takustr 7 D-14195 Berlin Germany

ISBN: (纸本)9789729959646

mixed-integer linear programming (MILP) methods have been applied widely to optimal design of energy supply systems in consideration of multi-period operation. A hierarchical MILP method has been proposed to solve such optimal design problems efficiently. An original problem has been solved by dividing it into a relaxed optimal design problem at the upper level and optimal operation problems which are independent of one another at the lower level. In addition, some strategies have been proposed to enhance the computation efficiency furthermore. In this paper, a method of reducing model by time aggregation is proposed as a novel strategy to search design candidates efficiently in the relaxed optimal design problem at the upper level. In addition, the previous strategies are modified in accordance with the novel strategy. This method is realized only by clustering periods and averaging energy demands for clustered periods, while it guarantees to derive the optimal solution. Thus, it may decrease the computation time at the upper level. Through a case study on the optimal design of a gas turbine cogeneration system, it is clarified how the model reduction is effective to enhance the computation efficiency in comparison and combination with the modified previous strategies. (C) 2019 Elsevier Ltd. All rights reserved.

关键词： Energy supply Optimal design mixed-integer linear programming Hierarchical optimization Model reduction Time aggregation

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Small-m method for detecting all longest paths

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OPSEARCH 2019年第3期56卷 824-839页

作者： Goto, Hiroyuki Murray, Alan T. Univ Calif Santa Barbara Santa Barbara CA 93106 USA

Given a weighted directed graph without positive cycles, we construct a framework to detect all longest paths for pairs of nodes in a network. The interest is to identify all routes with the highest cumulative cost for each source-destination pair. The significance and need for this arises in several scheduling contexts, an example of which is called critical chain project management. All longest routes are enumerated and compared for each output to determine a bottleneck path referred to as critical chain. Besides finding longest paths, minimizing duration needs to be considered. This indicates that multiple types of optimization problems coexist in one methodology. We thus aim to contain the longest-paths problem through constraints, for which an optimal solution that minimizes duration can be detected by solving a single optimization problem. The framework is reduced to a constraint satisfaction problem in a mixed-integer linear-programming context, and the solution can be derived using a general purpose solver. Optimality for the longest-paths problem is proven using the small-m method. Since the developed framework does not require an objective function specification, the methodology can also be incorporated within other optimization based problem contexts.

关键词： Critical chain project management All longest paths mixed-integer linear programming Constraint satisfaction

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A variability reduction method for the operating room scheduling problem under uncertainty using CVaR

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OPERATIONS RESEARCH FOR HEALTH CARE 2019年 20卷 25-32页

作者： Najjarbashi, Amirhossein Lim, Gino J. Univ Houston Dept Ind Engn 4800 Calhoun Rd Houston TX 77204 USA

Uncertain surgery durations in Operating Rooms (OR) can cause a large deviation from the expected completion time of all surgery cases scheduled for each day. When the deviation is significantly large, it causes an extended overtime for the surgical team to complete the scheduled cases, and it often creates unnecessarily excessive idle times. As a result, the hospital will lose revenue opportunities. To address this issue, this paper presents a risk-based solution approach using the concept of Conditional Value-at-Risk (CVaR) to reduce variability on overtime, idle time, and associated costs in a daily OR scheduling problem. The OR scheduling problem is formulated as a stochastic mixed-integer linear programming (SMILP) model, where a surgery duration follows a probability distribution function. The objective of the SMILP model is to minimize the CVaR of overtime and idle time costs. Numerical experiments are conducted on real-life benchmark instances, and showed that CVaR outperformed the widely used expected value (EV) approach in reducing variance of the total cost. As compared to the EV in terms of the total cost, the CVaR reduced the variance by 37%, produced a 25% lower interquartile range, and 24% lower median absolute deviation at a slight increase (4%) in the expected value. (C) 2019 Elsevier Ltd. All rights reserved.

关键词： Operating room scheduling Uncertain surgery duration Conditional value-at-risk mixed-integer linear programming Risk

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