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Mathematical models to improve the current practice in a Home Healthcare Unit

OR SPECTRUM 2020年第1期42卷 43-74页

作者： Quintanilla, Sacramento Ballestin, Francisco Perez, Angeles Univ Valencia Dept Matemat Econ & Empresa Valencia 46022 Spain

This paper addresses a home healthcare routing problem in which doctors and nurses visit patients at their homes to provide services. We consider a real-world home healthcare service arising in a particular hospital in Spain. Doctors and nurses are distributed in teams and travel by taxi;taxis transport a pre-defined set of workers who travel together the whole route. The objective is to minimise the transportation costs related to the total taxi journey time, including travelling and waiting costs. The paper presents a mathematical model that considers these current policies and permits the problem to be solved optimally. The paper also explores, after reviewing the hospital's current model, the benefits that can be obtained by changing some of the current policies of the hospital. In this way, a new model is proposed based on two sustainable strategies that can be extended to other home service fields: (1) workers can walk between houses and (2) the workers transported by a taxi may change during the route. A complex nonlinear mathematical model is presented, and a metaheuristic is designed to provide quality solutions. Computational tests on a set of instances based on real-world data estimate the gap between the solutions of both models.

关键词： Home healthcare problem Heuristics Nonlinear integer programming linear integer programming

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Managing aquatic invasions: Optimal locations and operating times for watercraft inspection stations

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JOURNAL OF ENVIRONMENTAL MANAGEMENT 2021年 283卷 111923-111923页

作者： Fischer, Samuel M. Beck, Martina Herborg, Leif-Matthias Lewis, Mark A. Univ Alberta Dept Math & Stat Sci 632 Cent Acad Bldg Edmonton AB T6G 2G1 Canada BC Minist Environm & Climate Change Strategy Conservat Sci Sect Victoria BC Canada Fisheries & Oceans Canada Inst Ocean Sci Sidney BC Canada Univ Alberta Dept Biol Sci Edmonton AB Canada

Aquatic invasive species (AIS) cause significant ecological and economic damages around the world. A major spread mechanism for AIS is traffic of boaters transporting their watercraft from invaded to uninvaded water bodies. To inhibit the spread of AIS, Canadian provinces and American states often set up watercraft inspection stations at roadsides, where potentially infested boats are screened for AIS and, if necessary, decontaminated. However, since budgets for AIS control are limited, watercraft inspection stations can only be operated at specific locations and daytimes. Though theoretical studies provide managers with general guidelines for AIS management, more specific results are needed to determine when and where watercraft inspections would be most effective. This is the subject of this paper. We show how linear integer programming techniques can be used to optimize watercraft inspection policies under budget constraints. We introduce our approach as a general framework and apply it to the prevention of the spread of zebra and quagga mussels (Dreissena spp.) to the Canadian province of British Columbia. We consider multiple scenarios and show how variations in budget constraints, propagule sources, and model uncertainty affect the optimal policy. Based on these results, we identify simple, generally applicable principles for optimal AIS management.

关键词： Aquatic invasive species linear integer programming Optimal management Spatially explicit Zebra mussel

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Minimizing the number of robots required for a Robotic Process Automation (RPA) problem

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Procedia Computer Science 2021年 192卷 709-716页

作者： Sara Séguin Hugo Tremblay Iméne Benkalaï David-Emmanuel Perron-Chouinard Xavier Lebeuf Université du Québec à Chicoutimi 555 boul. de l’Université Saguenay G7H2B1 Canada Group for Research in Decision Analysis (GERAD) 3000 ch. de la Côte-Sainte-Catherine Montréal H3T2A7 Canada

Robotic Process Automation (RPA) is used in various fields of human activity in order to implement faster and more secure processes through a reduction in the risks or errors but also an increase in the productivity rates. The increase of its use and importance calls for evermore efficient solution methods for this problem. In this paper, the RPA is addressed in the context of a financial institution. The problem consists in assigning transactions to software robots, where each transaction type has a different clearance date and a different processing time. First, four heuristics are used to compute an upper bound on the number of required software robots. Then, this bound is given as a parameter to an integer linear program, which is used to assign the transactions to the different robots. The quality of the solutions is assessed by an extensive experimental study on a set of 39,000 instances. The results show that two heuristics outperform the others and allow for a faster resolution by the integer linear program which in turn finds the optimal solution for most of the instances within a timeout of 60 seconds.

关键词： Robotic process automation linear integer programming bin packing heuristics upper bound

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Convexity Properties for a Function of Two integer Variables

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American Journal of Operations Research 2021年第6期11卷 253-256页

作者： Sara Nourazari Hillel Kumin Department of Health Care Administration California State University Long Beach CA USA School of Industrial and Systems Engineering University of Oklahoma Norman OK USA

Sufficient conditions are given for any local minimum of a function of two integer variables to be a global minimum. An example is given to show that a function of two integer variables need not be discrete convex for... 详细信息

关键词： linear integer programming Convexity

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The Tick Formulation for deadlock detection and avoidance in railways traffic control

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JOURNAL OF RAIL TRANSPORT PLANNING & MANAGEMENT 2021年 17卷

作者： Dal Sasso, Veronica Lamorgese, Leonardo Mannino, Carlo Onofri, Andrea Ventura, Paolo Optrail Viale Marco Polo 59 I-00154 Rome Italy SINTEF Digital Oslo Norway Univ Oslo Oslo Norway IASI CNR Rome Italy

Wrong dispatching decisions may lead to deadlocks, where trains reciprocally block resources necessary to reach their destinations. It is crucial to develop tools to detect such potential deadlocks on time, in order to reverse the decisions previously taken by dispatchers or to take recovery actions. In this paper we present a new 0,1 linear formulation for detecting deadlocks and optimally park the involved trains to reduce congestion around the affected area. We discuss computational results on some realistic randomly generated instances to show the validity of the approach, as well as its limits.

关键词： Deadlock detection Railways networks linear integer programming Tick formulation

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Tripartite Active Learning for Interactive Anomaly Discovery

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IEEE ACCESS 2019年 7卷 63195-63203页

作者： Zhu, Yanqiao Yang, Kai Tongji Univ Sch Software Engn Shanghai 201800 Peoples R China Tongji Univ Dept Comp Sci Shanghai 201800 Peoples R China

Most existing approaches to anomaly detection focus on statistical features of the data. However, in many cases, users are merely interested in a subset of the statistical outliers depending on the specific domain of interest, e.g., network attacks or financial fraud. The instruction from human experts is therefore indispensable in building predictive models in such applications. However, obtaining labels from human experts is time-consuming and expensive. Obtaining labels from nonexpert labelers are relatively easy and cost-effective. However, the labeling accuracy of a nonexpert is usually difficult to assess. Therefore, it remains open to leverage both the machine intelligence and the knowledge from labelers with diverse backgrounds to construct a machine learning model for domain-specific anomaly detection. To this end, this paper proposes a framework of tripartite active learning for interactive anomaly discovery in large datasets based on crowdsourced labels. This tripartite active learning method consists of two stages. In the first stage, an unsupervised learning algorithm is employed to extract statistical outliers from the dataset. This algorithm is of low computational complexity as well as memory requirement and thus well suited for large datasets. We then develop an iterative algorithm consisting of two steps. The algorithm first evaluates and trains labelers based on gold instances provided by the expert labelers. Then, it assigns the most informative samples to its most confident labeler for relabeling and update the detector based on new labels. The capacity constraints are taken into account in the active learning approach to guarantee the fair allocation of labeling instances as well as robustness against erroneous labels. It is seen through experiments that the proposed algorithm provides an effective means for interactive anomaly detection. As far as we are aware of, this is the first work that considers designing a tripartite machine learning sy

关键词： Active learning interactive artificial intelligence anomaly detection linear integer programming human training

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Operation Identification of Electrical Appliance Considering Time Correlation Between Operation States 8

Operation Identification of Electrical Appliance Considering...

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IEEE 8th Joint International Information Technology and Artificial Intelligence Conference (ITAIC)

作者： Huang, Yuqian Wu, Shuomin Li, Yaping Wang, Ying Zhang, Kaifeng Southeast Univ Minist Educ Key Lab Measurement & Control Complex Syst Engn Nanjing 210096 Jiangsu Peoples R China China Elect Power Res Inst Nanjing Nanjing 210003 Jiangsu Peoples R China

ISBN: (纸本)9781538681787

a new method for identifying the operation of electrical appliances is proposed in this paper, which considers the time correlation between different operating states of the same electrical appliance. Firstly, the improved k-means clustering algorithm is used to obtain the active power values of each operating state for electrical appliances;Then several independent state time series are established to comprehensively cover the 10-min sampling interval for the same electrical appliance;Finally, constraints are determined based on the time correlation between operating states in the same state time series, the operation of electrical appliances will be identified by integer programming algorithm. The experiments results show that the algorithm proposed identify the instants of appliances ON/OFF and the times of start and stop for appliances accurately.

关键词： operation status identification of the electrical appliances time correlation state time series set linear integer programming

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Joint Optimization of Gateway Placement and Multi-hop Routing for the Internet of Things 6

Joint Optimization of Gateway Placement and Multi-hop Routin...

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6th National-Foundation-for Science-and-Technology-Development (NAFOSTED) Conference on Information and Computer Science (NICS)

作者： Hoai-Nam Chu Tuan-Minh Pham Univ Transport & Commun Dept Telecommun Engn Hanoi Vietnam Phenikaa Univ Fac Comp Sci Hanoi Vietnam

ISBN: (数字)9781728151632

ISBN: (纸本)9781728151632

The Internet of Things (IoT) has materialized smart homes, smart manufacturing, and smart cities for a better quality of life and new industrial opportunities. In an IoT network, a massive number of devices might lead to a serious problem of scalable performance. A possible approach for the scalability problem is to use the support of multi-hop routing for data communication and to group IoT devices into clusters. In this paper, we consider the joint optimization problem of gateway placement in a cluster and routing for an IoT network supporting multihop communication. We first formulate the problem as a Mixed integer linear programming (MILP) model for obtaining the optimal solution. We then develop an approximation algorithm for addressing the problem in a large-scale IoT network. The evaluation results under a set of scenarios with various topologies and parameters show that the proposed algorithm achieves the results close to the optimal solution with a huge decrease in computation time. Our solution allows an IoT service provider to determine the optimal solution for the deployment of gateways and the optimal routing with a performance constraint in an IoT network.

关键词： IoT optimization multi-hop routing linear integer programming

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Operations Research Frameworks for Improving Make-Ahead Drug Policies at Outpatient Chemotherapy Infusion Centers

Operations Research Frameworks for Improving Make-Ahead Drug...

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作者： Richardson, Donald University of Michigan

Outpatient chemotherapy infusion is one of the most common forms of treatment used to cure, control, and ease symptoms of cancer. Patients who require outpatient chemotherapy infusion undergo lengthy and physically demanding infusion sessions over the course of their treatment. While the frequency and duration of visits vary by patient, drug, and cancer type, most patients will require several treatments over the course of months or years to complete their regimen/treat their disease. Receiving infusion is just one part of the complex treatment process. Patients may have their blood work done, wait for the results to process, visit their oncologist, wait on their order to be placed by their oncologist and prepared by the pharmacy, and then have the infusion administered by infusion clinic staff. Each step introduces randomness which can lead to propagated delays. These delays negatively affect patients as well as clinical operation cost and staff workload. We focus on optimizing drug preparation at the pharmacy to reduce patient delays. Drugs can be prepared the morning before patients arrive to prevent the patient from waiting the additional time needed to prepare their prescribed drugs in addition to any other wait time incurred during peak pharmacy hours. However, patients scheduled for outpatient chemotherapy infusion sometimes may need to cancel at the last minute even after arriving for their appointment (i.e. patient may be deemed too ill to receive treatment). This results in the health system incurring waste cost if the drug was made ahead since the drugs are patient specific and have a short shelf life. Infusion centers must implement policies to balance this potential waste cost with the time savings for their patients and staff. In support of this effort, this dissertation focuses on methods and strategies to improve the process flow of chemotherapy infusion outpatients by optimizing pharmacy make-ahead policies. We propose using three different methods

关键词： linear integer programming Simulation Predictive Modeling Cancer Center Pharmacy Thesis

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Construction of Polygonal Designs Using linear integer programming

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COMMUNICATIONS IN STATISTICS-THEORY AND METHODS 2011年第10期40卷 1787-1794页

作者： Mandal, B. N. Gupta, V. K. Parsad, Rajender Indian Inst Soil Sci Bhopal 462038 MP India Indian Agr Res Inst New Delhi India

This article proposes a new linear integer programming approach to obtain polygonal designs for given number of treatments v, block size k, concurrence of treatments separated by a distance of m+1 or more as and all other concurrences as zero, [image omitted]. The main feature of the proposed approach is that it directly identifies the required incidence vectors for generating a polygonal design. Using the proposed approach, a complete solution is provided for constructing polygonal designs for number of treatments v100, block size k=3, =1, 2 and [image omitted].

关键词： Balanced sampling plans excluding adjacent units Incidence vectors Incomplete block designs linear integer programming Polygonal designs

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