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integer programming models for deployment of airport baggage screening security devices

OPTIMIZATION AND ENGINEERING 2005年第3期6卷 339-359页

作者： Jacobson, SH McLay, LA Virta, JL Kobza, JE Univ Illinois Dept Mech & Ind Engn Simulat & Optimizat Lab Urbana IL 61801 USA Texas Tech Univ Dept Ind Engn Lubbock TX 79409 USA

Aviation security is an important problem of national interest and concern. Baggage screening security devices and operations at airports throughout the United States provide an important defense against terrorist actions targeted at commercial aircraft. Determining where to deploy such devices, and how to best use them can be quite challenging. This paper presents NP-complete decision problems concerning the deployment and utilization of baggage screening security devices. These problems incorporate three different deployment performance measures: uncovered baggage segments, uncovered flight segments, and uncovered passenger segments. integer programming models are formulated to address optimization versions of these problems and to identify optimal baggage screening security device deployments (i.e., determine the number and type of baggage screening security devices that should be placed at different airports, and determining which baggage should be screened with such devices). The models are illustrated with an example that incorporates data extracted from the Official Airline Guide (OAG).

关键词： aviation security homeland security NP-completeness integer programming models cost analysis

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Theoretical analysis of integer programming models for the two-dimensional two-staged knapsack problem

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OPTIMIZATION LETTERS 2024年 1-32页

作者： Kang, Suho Kim, Junyoung Joung, Seulgi Lee, Kyungsik Seoul Natl Univ Dept Ind Engn 1 Gwanak Ro Seoul 08826 South Korea Ajou Univ Dept Ind Engn 206 Worldcup Ro Suwon 16499 South Korea Myongji Univ Dept Business Adm 34 Geobukgol Ro Seoul 03674 South Korea

In this study, we theoretically compare integer programming models for the two-dimensional two-staged knapsack problem. Including the well-known level packing model, we introduce two pattern-based models called the strip packing model and the staged pattern model derived from integer programming models for the two-dimensional two-staged cutting stock problem. We show that the level packing model provides weaker linear programming (LP) relaxation bounds than pattern-based models. Furthermore, we also present upper bounds on the LP-relaxation bound of the level packing model, which can be obtained from the LP-relaxation bounds of the pattern-based models.

关键词： Two-dimensional two-staged knapsack problem integer programming models Level packing model Strip packing model Staged pattern model LP-relaxation

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Mixed integer programming models for machine learning and discriminant analysis

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ZEITSCHRIFT FUR ANGEWANDTE MATHEMATIK UND MECHANIK 1996年第s3期76卷 491-492页

作者： Lee, EK Gallagher, R Paterson, D COLUMBIA PRESBYTERIAN MED CTR DEPT MED INFORMATNEW YORKNY 10032 UNIV MONTANA DEPT MATH SCIMISSOULAMT 59812

We present exact and heuristic mixed 0/1 integer programming models for approaching classification, problems arising in discriminant analysis. Numerical results on problem instances derived from three well-known data ... 详细信息

关键词： Heuristics Exact Dataset integer programming models Machine Learning WWOX gene Mixing discriminant analysis

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integer programming models and algorithms for molecular classification of cancer from microarray data 05

Integer programming models and algorithms for molecular clas...

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Australasian Computer Science Conference

作者： Regina Berretta Alexandre Mendes Pablo Moscato University of Newcastle Callaghan NSW Australia

ISBN: (纸本)9781920682200

Novel, high-throughput technologies are challenging the core of algorithmic methods available in Computer Science. Microarray technologies give Life Sciences researchers the opportunity to simultaneously measure thousands of gene expression levels under different conditions or coming from different cell lines. With appropriate data mining models and algorithms, this would lead to a systematic exploration of molecular classification of cancer, just one among many other exciting applications. The aim of this paper is to present a unified mathematical formalization for different feature selection problems and investigate their performance in classification of cancer cell-lines. We also present some results using the NCI60 dataset.

关键词： feature selection Feature extraction integer programming models algorithms Taxonomy Microarray Cell Line

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Survey of mathematical programming models in air pollution management

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EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 1997年第1期96卷 1-35页

作者： Cooper, WW Hemphill, H Huang, Z Li, S Lelas, V Sullivan, DW TEXAS NAT RESOURCES CONSERVAT COMMISS OFF AIR MONITORING OPERATAUSTINTX 78711 ADELPHI UNIV NEW YORKNY 11530

This paper surveys the current state of the literature in management science/operations research approaches to air pollution management, After introducing suitable background we provide some of the institutional and legal framework needed to understand the continuing regulatory efforts in United States. Attention is then turned to mathematical programming models ranging from fairly simple deterministic linear programs to quite sophisticated stochastic models which have appeared in the literature dealing with these topics, This is followed by extensions reflecting some of the work we have undertaken in association with the Texas Natural Resource Conservation Commission, a regulatory agency in Texas, Application and potential use of models is the central theme of this survey, Issues for future research are presented at the end and an extensive list of publications is provided in the references at the end of the article. Principal air quality issues of local, national, and international concern are listed below in increasing order of difficulty based on the number of different types of pollutants and problems in quantification of the risks the pollutants pose: 1. Stratospheric ozone depletion: one relatively easily controllable class of trace gases - ozone depleting chemicals, or ODCs, principally chloroflurocarbons (CFCs) - with relatively well quantified risks;2. Criteria pollutants: six common pollutants - ozone (O-3), carbon monoxide (CO), sulfur dioxide (SO2), nitrogen dioxide (NO2), lead (Pb), and particulate matter less than 10 microns in size (PM10) - regulated since 1970 in the U.S. and presenting relatively well quantified risks;3. Acid precipitation: two relatively easily controllable classes of trace gases - oxides of nitrogen (NOx) and oxides of sulfur (SOx) with relatively well quantified risks;4. Global warming/climate change: a few difficult to control trace gases - principally carbon dioxide (CO2), methane (CH4), nitrous oxide (N2O), and CFCs - with hi

关键词： Optimization methods publications integer programming models Pollutant mathematical programming linear programming models trace gases pollution management

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TECHNIQUES FOR SELECTIVE REVALIDATION

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IEEE SOFTWARE 1990年第1期7卷 31-36页

作者： HARTMANN, J ROBSON, DJ Cent. Software Maint. Univ. Durham Durham DH1 3LE UK

Discusses approaches to revalidation of modified software. Classification of types of changes made to a system during maintenance; Two major problems in regression testing; Test-suite maintenance.

关键词： KF CASING INSPECTION integer programming models Writers MODIFICATION

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USING SEPARATION ALGORITHMS TO GENERATE MIXED integer MODEL REFORMULATIONS

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OPERATIONS RESEARCH LETTERS 1991年第3期10卷 119-128页

作者： MARTIN, RK Graduate School of Business University of Chicago 1101 East 58th Street Chicago IL 60637 USA

The linear relaxation of mixed integer programming models can be strengthened by introducing auxiliary variables. We develop a new method for generating auxiliary variable reformulations for problems where the separation algorithm for finding violated cuts can be formulated as a linear program. Our results have important consequences for integrality proofs and efficient formulations.

关键词： integer programming models CUTTING PLANE ALGORITHMS MODEL REFORMULATION

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Assignment of duplicate storage locations in distribution centres to minimise walking distance in order picking

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INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH 2021年第15期59卷 4457-4471页

作者： Jiang, Wei Liu, Jiyin Dong, Yun Wang, Li Zhejiang Normal Univ Coll Engn Key Lab Unban Rail Transit Intelligent Operat & M Jinhua Zhejiang Peoples R China Loughborough Univ Sch Business & Econ Loughborough Leics England Northeastern Univ Minist Educ Key Lab Data Analyt & Optimizat Smart Ind Shenyang Peoples R China Univ Sci & Technol Liaoning Sch Elect & Informat Engn Anshan Peoples R China

With the rapid development of e-commerce, the orders processed in B2C warehouses are characterised by heterogeneous and small volume. The traditional storage assignment strategies used in the picker-to-parts warehouses do not have advantage any more. In this case, the scattered storage strategy is a good alternative. In this paper, we study a new scattered storage strategy that allows the same product to be placed in multiple storage locations. The correlation between products which reflects how frequently any two products will be ordered together in the same order is considered. The problem is formulated as a 0-1 integer programming model to minimise the weighted sum of distances between the products, with weight being the elements of the correlation matrix. To solve large-scale problems, a GA and a basic PSO algorithm are developed. To improve solution quality, a new PSO algorithm based on the problem characteristic is designed and a hybrid algorithm combing it with GA is proposed. Experiments show that the solutions of these algorithms are close to the optimal solutions for the small-sale problems. For larger problems, the specially designed new PSO greatly improves solution quality as compared to the basic algorithms and the hybrid algorithm makes further improvement.

关键词： storage location assignment scattered storage strategy integer programming models genetic algorithm particle swarm optimisation

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An exact approach for the balanced k-way partitioning problem with weight constraints and its application to sports team realignment

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JOURNAL OF COMBINATORIAL OPTIMIZATION 2018年第3期36卷 916-936页

作者： Recalde, Diego Severin, Daniel Torres, Ramiro Vaca, Polo Escuela Politec Nacl Dept Matemat Ladron Guevara E11-253 Quito 170109 Ecuador Escuela Politec Nacl Res Ctr Math Modelling MODEMAT Quito Ecuador Univ Nacl Rosario FCEIA Rosario Santa Fe Argentina Consejo Nacl Invest Cient & Tecn Rosario Santa Fe Argentina

In this work a balanced k-way partitioning problem with weight constraints is defined to model the sports team realignment. Sports teams must be partitioned into a fixed number of groups according to some regulations, where the total distance of the road trips that all teams must travel to play a double round robin tournament in each group is minimized. Two integer programming formulations for this problem are introduced, and the validity of three families of inequalities associated to the polytope of these formulations is proved. The performance of a tabu search procedure and a branch and cut algorithm, which uses the valid inequalities as cuts, is evaluated over simulated and real-world instances. In particular, an optimal solution for the realignment of the Ecuadorian football league is reported and the methodology can be suitable adapted for the realignment of other sports leagues.

关键词： integer programming models Graph partitioning Tabu search Sports team realignment

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Genetic Algorithm-Based Particle Swarm Optimization Approach to Reschedule High-Speed Railway Timetables: A Case Study in China

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JOURNAL OF ADVANCED TRANSPORTATION 2019年第Pt.2期2019卷 6090742.1-6090742.12页

作者： Wang, Mingming Wang, Li Xu, Xinyue Qin, Yong Qin, Lingqiao Beijing Jiaotong Univ State Key Lab Railway Traff Control & Safety Sch Traff & Transportat Beijing Peoples R China Beijing Jiaotong Univ Sch Traff & Transportat Beijing Peoples R China Beijing Jiaotong Univ State Key Lab Railway Traff Control & Safety Beijing Peoples R China Univ Wisconsin Dept Civil & Environm Engn TOPS Lab Madison WI 53706 USA

In this study, a mixed integer programming model is proposed to address timetable rescheduling problem under primary delays. The model considers timetable rescheduling strategies such as retiming, reordering, and adjusting stop pattern. A genetic algorithmbased particle swarm optimization algorithm is developed where position vector and genetic evolution operators are reconstructed based on departure and arrival time of each train at stations. Finally, a numerical experiment of Beijing-Shanghai high-speed railway corridor is implemented to test the proposed model and algorithm. The results show that the objective value of proposed method is decreased by 15.6%, 48.8%, and 25.7% compared with the first-come-first-service strategy, the first-schedule-first-service strategy, and the particle swarm optimization, respectively. The gap between the best solution obtained by the proposed method and the optimwn solution computed by CPLEX solver is around 19.6%. All delay cases are addressed within acceptable time (within 1.5 min). Moreover, the case study gives insight into the correlation between delay propagation and headway. The primary delays occur in high-density period (scheduled headway closes to the minimum headway), which results in a great delay propagation.

关键词： Particle swarm optimization delayed crack propagation integer programming models arrival time Case studies high-speed railway Rescheduling Position vector

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