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2021 CIE International Conference on Radar, Radar 2021

作者： Miao, Ke Zhang, Yi Yao, Chen Sun, Houjun Beijing Key Laboratory of Millimeter Wave and Terahertz Techniques School of Information and Electronics Beijing Institute of Technology Beijing China School of Physics Beijing Institute of Technology Beijing China

ISBN: (纸本)9781665498142

Phase-only tapering for sidelobe suppression is a simple method of phased array design due to the simplification of antenna manufacturing. When using digital phase shifters, considering the quantization of the phase, we employ integer linear programming to adjust the phased shifter and get a better pattern. The proposed method combines a fast sidelobe formula with a power reduction mathematical technique. Finally, we conduct numeric experiments to verify the proposed method. © 2021 IEEE.

关键词： array synthesis integer linear programming phase-only tapering sidelobe suppression

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integer linear programming-based multi-objective scheduling for scientific workflows in multi-cloud environments

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JOURNAL OF SUPERCOMPUTING 2019年第10期75卷 6683-6709页

作者： Mohammadi, Somayeh PourKarimi, Latif Pedram, Hossein Islamic Azad Univ Sci & Res Branch Dept Comp Engn Tehran Iran Razi Univ Dept Math Kermanshah Iran Amirkabir Univ Technol Dept Comp Engn Tehran Iran

Scientific communities are motivated to schedule the data-intensive scientific workflows in multi-cloud environments, where considerable diverse resources are provided by multiple clouds and resource limitation imposed by individual clouds is overcome. However, this scheduling involves two conflicting objectives: minimizing cost and makespan. In general, dealing with such conflicting criteria is a difficult task. But fortunately recent efficient methods for solving multi-objective optimization problems motivated us to provide a multi-objective model considering minimization of cost and makespan as objectives. For solving this model, we use different scalarization procedures such as weighted-sum, Benson's scalarization and weighted min-max under different scenarios. Moreover, we investigate the stability of obtained solutions and propose a new approach for determining the most stable solution related to weighted-sum and weighted min-max as post-optimality analysis. Results indicate that our proposed weighted-sum approach outperforms the previously developed methods in terms of hypervolume.

关键词： Multi-cloud Workflow scheduling Multi-objective optimization integer linear programming

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Alignment of biological networks by integer linear programming: virus-host protein-protein interaction networks

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BMC BIOINFORMATICS 2020年第Sup6期21卷 434-434页

作者： Llabres, Merce Riera, Gabriel Rossello, Francesc Valiente, Gabriel Univ Balearic Isl Dept Math & Comp Sci E-07122 Palma De Mallorca Spain Balearic Isl Hlth Res Inst E-07010 Palma De Mallorca Spain Tech Univ Catalonia Algorithms Bioinformat Complex & Formal Methods R E-08034 Barcelona Spain

BackgroundThe alignment of protein-protein interaction networks was recently formulated as an integer quadratic programming problem, along with a linearization that can be solved by integer linear programming software tools. However, the resulting integer linear program has a huge number of variables and constraints, rendering it of no practical *** present a compact integer linear programming reformulation of the protein-protein interaction network alignment problem, which can be solved using state-of-the-art mathematical modeling and integer linear programming software tools, along with empirical results showing that small biological networks, such as virus-host protein-protein interaction networks, can be aligned in a reasonable amount of time on a personal computer and the resulting alignments are structurally coherent and biologically *** implementation of the integer linear programming reformulation using current mathematical modeling and integer linear programming software tools provided biologically meaningful alignments of virus-host protein-protein interaction networks.

关键词： Systems biology Virus-host protein-protein interaction integer linear programming Network alignment Graph matching

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Using integer linear programming to minimize the embodied CO2 emissions of the opaque part of a facade

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BUILDING AND ENVIRONMENT 2020年 177卷 106883-106883页

作者： Soler, David Salandin, Andrea Bevivino, Michele Univ Politecn Valencia Inst Univ Matemat Multidisciplinar Cami Vera S-N Valencia 46022 Spain Univ Politecn Valencia Ctr Tecnol Fis Cami Vera S-N Valencia 46022 Spain Via Fiume 6 I-39100 Bolzano Italy

Buildings are responsible for about 36% of the CO2 emissions in Europe but there is a significant potential to reduce these emissions. This paper deals with the embodied CO2 emissions of the opaque part of a facade, which include the life cycle of any material used in its construction: excavation, processing, construction, operation, maintenance, demolition and waste or recycling. With the aim of minimizing such embodied CO2 emissions, an integer linear programming problem is presented, in which CO2 emissions are minimized depending on other parameters involved in the construction of the facade, like the maximal thermal transmittance allowed by current legislation, thickness of the wall, budget, availability of materials for the different layers of the wall, etc. The paper also shows a case study based on a constructive solution for the opaque part of the envelope defined by up to six layers, with more than 1.1 million possible combinations. This case study considers seventy scenarios depending on maximal allowed thermal transmittances and thickness intervals for five different technologies applied to the structural element of the wall. Results show that an adequate selection of materials can reduce the embodied CO2 emissions of the opaque part of the envelope up to 78.5% for similar values of transmittance and thickness.

关键词： Embodied CO2 emissions Thermal transmittance Facade integer linear programming Minimization

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An integer linear programming model to optimize the hub and spoke-based water desalinated transmission system

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JOURNAL OF WATER SUPPLY RESEARCH AND TECHNOLOGY-AQUA 2020年第6期69卷 604-615页

作者： Al Gahtani, Osama Saad Mrad, Mehdi King Saud Univ Coll Engn Dept Civil Engn Riyadh Saudi Arabia King Saud Univ Coll Engn Dept Ind Engn Riyadh Saudi Arabia

Desalinated water is becoming a significant resource in many countries. With limited water supply, several high-demand sites located far from the desalination plant and an efficient and cost-effective transmission and storage network have become critical. In many areas, desalinated water is not delivered efficiently through a pipeline and storage tank system capable of providing safe and cost-effective coverage to a wide range of demand sites. In addition, due to the limitation of transmission and storage distribution, many desalination plants are unable to achieve full production capacity. Many high-demand sites are at risk of disruption or water contamination due to single-source pipelines or desalination plants. In this study, the conceptual framework for an economically viable transmission and storage system helps decision-makers to define the requirements for the proper design of the system. The definition is introduced here to describe strategic tanks for efficient and economical supply allocation. The key aspects of setting up effective transmission and storage systems were outlined in the framework presented. To develop an efficient and cost-effective transmission and storage system, an integer linear program was constructed to solve the hub and spoke issue. A hypothetical example is presented and discussed to illustrate the advantages of the proposed model.

关键词： desalination integer linear programming pipeline storage tanks transmission

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A Parallelizable integer linear programming Approach for Tiling Finite Regions of the Plane with Polyominoes

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ALGORITHMS 2022年第5期15卷 164-164页

作者： Garvie, Marcus R. Burkardt, John Univ Guelph Dept Math & Stat Guelph ON N1G 2W1 Canada Univ Pittsburgh Dept Math Pittsburgh PA 15260 USA

The general problem of tiling finite regions of the plane with polyominoes is NP-complete, and so the associated computational geometry problem rapidly becomes intractable for large instances. Thus, the need to reduce algorithm complexity for tiling is important and continues as a fruitful area of research. Traditional approaches to tiling with polyominoes use backtracking, which is a refinement of the 'brute-force' solution procedure for exhaustively finding all solutions to a combinatorial search problem. In this work, we combine checkerboard colouring techniques with a recently introduced integer linear programming (ILP) technique for tiling with polyominoes. The colouring arguments often split large tiling problems into smaller subproblems, each represented as a separate ILP problem. Problems that are amenable to this approach are embarrassingly parallel, and our work provides proof of concept of a parallelizable algorithm. The main goal is to analyze when this approach yields a potential parallel speedup. The novel colouring technique shows excellent promise in yielding a parallel speedup for finding large tiling solutions with ILP, particularly when we seek a single (optimal) solution. We also classify the tiling problems that result from applying our colouring technique according to different criteria and compute representative examples using a combination of MATLAB and CPLEX, a commercial optimization package that can solve ILP problems. The collections of MATLAB programs PARIOMINOES (v3.0.0) and POLYOMINOES (v2.1.4) used to construct the ILP problems are freely available for download.

关键词： tiling with polyominoes checkerboard colouring arguments integer linear programming parallelizable algorithm algorithm complexity MATLAB CPLEX

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An integer linear programming model for efficient scheduling of UGV tasks in precision agriculture under human supervision

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COMPUTERS & OPERATIONS RESEARCH 2020年 114卷 104826-000页

作者： Tiotsop, Lohic Fotio Servetti, Antonio Masala, Enrico Politecn Torino Control & Comp Engn Dept Corso Duca Abruzzi 24 I-10129 Turin Italy

In precision agriculture more and more robots are being used to perform tasks that may include some farming activities, such as pruning, inspection or spraying, assigned to the robot as a result of a previous analysis activity or autonomously identified by the machine itself. In this sensitive scenario, reporting difficult situations to a decision maker, e.g., a human operator or some sophisticated software tools that cannot be integrated with the robot, could be useful to perform the correct action that the machine has to execute. Unfortunately, this key aspect is still neglected in current literature that focuses, instead, on fully automated operations by robots. Moreover, it is necessary to consider that in rural areas it often happens that successful data communication can only be achieved in certain locations in the field. In this context, we aim to address all the previous shortcomings by formulating a more comprehensive optimization problem, which also models the necessity to report to a central location and get instructions on the task to be done before proceeding to perform each action. After presenting two alternative analytical formulations of the problem, i.e. an integer linear programming model (ILP) and a mixed integer linear programming model, we propose a branch and bound algorithm that is guaranteed to find the global minimum cost solution in terms of navigation time. Simulation results show that our proposed algorithm performs about 20 to 30 times faster with respect to commercial linear programming solvers using any of the two analytical models proposed. Moreover, we also propose further improvements to reduce computational time while maintaining solution optimality. Finally, some insight into the development of future heuristics is given by analyzing the speed of convergence towards the optimal solution. (C) 2019 Elsevier Ltd. All rights reserved.

关键词： Data acquisition Farming activities UGV Navigation integer linear programming Service robotics

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CONSTRAINED ROLE-ENGINEERING OPTIMIZATION USING BOOLEAN MATRIX DECOMPOSITION AND integer linear programming TECHNIQUES

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INTERNATIONAL JOURNAL OF INNOVATIVE COMPUTING INFORMATION AND CONTROL 2022年第4期18卷 1037-1053页

作者： Sun, Wei Xinyang Normal Univ Sch Comp & Informat Technol 237 Nanhu Rd Xinyang 464000 Peoples R China

Role-based access control (RBAC) is a widely popular access control mechanism because of its convenience for authorization administration, as well as various security policies, such as the separation-of-duty constraint and cardinality constraint. In recent few years, role-engineering technology has emerged as an efficient approach to constructing optimal RBAC systems. However, the bottom-up approaches lack flexibility and extendibility as the organizational requirements change dynamically. Furthermore, most conventional methods do not consider multiple cardinality constraints. To address these issues, this paper proposes a novel role-engineering method. First, to flexibly meet diverse organizational requirements while enhancing the security of role-engineering processes, according to different evaluation measures or optimization objectives, we define several variants of the optimization problem with the cardinality constraint using Boolean matrix decomposition technique. Second, we present a unified modelling framework for these variants using integer linear programming technique, and propose heuristic optimization algorithms in the bottom-up way, in order to verify whether the constraints can be satisfied in the constructed access control model. The experimental evaluations demonstrate the effectiveness and efficiency of the proposed method.

关键词： Role-based access control Role engineering Cardinality constraint Boolean matrix decomposition integer linear programming

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Gamma deployment problem in grids: hardness and new integer linear programming formulation

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INTERNATIONAL TRANSACTIONS IN OPERATIONAL RESEARCH 2020年第6期27卷 2740-2759页

作者： Faraj, Marcelo Fonseca Urrutia, Sebastian Sarubbi, Joao F. M. Univ Fed Minas Gerais Comp Sci Dept BR-31270901 Belo Horizonte MG Brazil Univ Vienna Fac Comp Sci A-1010 Vienna Austria Molde Univ Coll Fac Logist N-6410 Molde Norway Fed Ctr Technol Educ Minas Gerais Comp Dept BR-30510000 Belo Horizonte MG Brazil

Vehicular networks are mobile networks designed for the domain of vehicles and pedestrians. These networks are an essential component of intelligent transportation systems and have the potential to ease traffic management, lower accident rates, and offer other solutions to smart cities. One of the most challenging aspects in the design of a vehicular network is the distribution of its infrastructure units, which are called roadside units (RSUs). In this work, we tackle the gamma deployment problem that consists of deploying the minimum number of RSUs in a vehicular network in accordance with a quality of service metric called gamma deployment. This metric defines a vehicle as covered if it connects to some RSUs at least once in a given time interval during its whole trip. Then, the metric parameterizes the minimum percentage of covered vehicles necessary to make a deployment acceptable or feasible. In this paper, we prove that the decision version of the gamma deployment problem in grids is NP-complete. Moreover, we correct the multiflow integer linear programming formulation present in the literature and introduce a new formulation based on set covering that is at least as strong as the multiflow formulation. In experiments with a commercial solver, the set covering formulation widely outperforms the multiflow formulation with respect to running time and linear programming relaxation gap.

关键词： gamma deployment complexity integer linear programming

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Learning feedback molecular network models using integer linear programming

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PHYSICAL BIOLOGY 2022年第6期19卷 066004-066004页

作者： Ozen, Mustafa Emamian, Effat S. Abdi, Ali Vanderbilt Univ Dept Biochem Nashville TN 37205 USA Adv Technol Novel Therapeut Millburn NJ 07041 USA New Jersey Inst Technol Dept Elect & Comp Engn Newark NJ 07102 USA New Jersey Inst Technol Dept Biol Sci Newark NJ 07102 USA

Analysis of intracellular molecular networks has many applications in understanding of the molecular bases of some complex diseases and finding effective therapeutic targets for drug development. To perform such analyses, the molecular networks need to be converted into computational models. In general, network models constructed using literature and pathway databases may not accurately predict experimental network data. This can be due to the incompleteness of literature on molecular pathways, the resources used to construct the networks, or some conflicting information in the resources. In this paper, we propose a network learning approach via an integer linear programming formulation that can systematically incorporate biological dynamics and regulatory mechanisms of molecular networks in the learning process. Moreover, we present a method to properly consider the feedback paths, while learning the network from data. Examples are also provided to show how one can apply the proposed learning approach to a network of interest. In particular, we apply the framework to the ERBB signaling network, to learn it from some experimental data. Overall, the proposed methods are useful for reducing the gap between the curated networks and experimental data, and result in calibrated networks that are more reliable for making biologically meaningful predictions.

关键词： feedbacks integer linear programming learning network models machine learning molecular networks network modeling

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