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11th International Symposium on Operations Research and its Applications(第11届运筹学及其应用国际研讨会)

作者： Ping Ji Jian Jin Department of Industrial and Systems Engineering The Hong Kong Polytechnic UniversityHong Kong The Hong Kong Polytechnic University Shenzhen Research Institute Shenzhen 518057 China

ISBN: (纸本)9781632665485

Many pairwise models are proposed for ranking problems in the field of information *** problems in the field of data mining also use pairwise ***,conventionally,these pairwise approaches are evaluated based evaluation *** original rating for a single document or instance is not explained faithfully,which makes these algorithms cannot be evaluated by standard evaluation metrics,such as Mean Average Precision and Normalized Discounted Cumulative Gain for ranking *** this research,the focus is on how to transform pairwise based results to the original ***,an integer linear programming model is formulated for this *** this algorithm,the objective is to minimize the number of conflicts for the predicted pairwise based relationship between instances by the assignment of rating *** example is presented in order to clarify the proposed integer linear programming *** validates the possibility to transform pairwise based results to the original ratings,which make them to be evaluated by standard evaluation metrics.

关键词： integer linear programming pairwise optimization

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Relaxed Connected Dominating Set Problem for Power System Cyber-Physical Security

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IEEE TRANSACTIONS ON CONTROL OF NETWORK SYSTEMS 2022年第4期9卷 1780-1792页

作者： Sou, Kin Cheong Lu, Jie Natl Sun Yat Sen Univ Dept Elect Engn Kaohsiung 804 Taiwan ShanghaiTech Univ Sch Informat Sci & Technol Shanghai 201210 Peoples R China

Motivated by power system cyber-physical security applications, this article investigates a variant of the connected dominating set problem called the relaxed connected dominating set (RCDS) problem, where between every two nodes in the solution dominating set there exists a path not traversing two consecutive nodes not in the set. The RCDS problem is NP-hard. To facilitate solving, presolving and problem reduction techniques are developed. In addition, three integer program formulations are obtained using single commodity flow, Dantzig-Fulkerson-Johnson and Miller-Tucker-Zemlin ideas to enforce graph connectedness. For a realistic power network repository (MATPOWER 7) including graphs with 70k nodes, our presolving and reduction procedures simplify problem instances to on average 30% of the original sizes. All reduced instances, when modeled by our formulations, can be solved with optimality gap less than 0.5% within 20 min using a PC with Gurobi 9.

关键词： Algorithm data reduction integer linear programming power system security

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Maximizing total early work in a distributed two-machine flow-shop

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NAVAL RESEARCH LOGISTICS 2022年第8期69卷 1124-1137页

作者： Dolgui, Alexandre Kovalyov, Mikhail Y. Lin, Bertrand M. T. IMT Atlantique LS2N CNRS Nantes 3 France Natl Acad Sci Belarus United Inst Informat Problems Minsk BELARUS Natl Yang Ming Chiao Tung Univ Inst Informat Management Hsinchu 300 Taiwan

The problem of maximizing total early work in a two-machine flow-shop, in which n jobs are to be scheduled subject to a common due date d, has been recently studied in the scheduling literature. An O(n(2)d(4)) time dynamic programming algorithm was presented first for the weighted case, and then for the unweighted case another O(n(2)d(2)) running time dynamic programming algorithm was proposed and converted into an O (n(4)/epsilon(2)) time fully polynomial time approximation scheme (FPTAS). By establishing new problem properties, we present an O(nd(2)) time dynamic programming algorithm and an O(n(3)/epsilon(2)) time FPTAS for the unweighted problem. We generalize the problem to a distributed setting of m parallel two-machine flow-shops, develop an O(nd(3m)) time dynamic programming algorithm, an O (n(3m+1)/epsilon(3m)) time FPTAS, and three integer linear programming (ILP) formulations for it. Computational experiments are conducted to appraise the proposed ILP models.

关键词： distributed flow-shop dynamic programming early work FPTAS integer linear programming scheduling two-machine flow-shop

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Assembling Close Strains in Metagenome Assemblies Using Discrete Optimization

Assembling Close Strains in Metagenome Assemblies Using Disc...

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17th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2024

作者： Truong, Tam Khac Minh Faure, Roland Andonov, Rumen Univ. Rennes INRIA RBA CNRS UMR 6074 Rennes France Brussels 1050 Belgium

Metagenomic assembly is essential for understanding microbial communities but faces challenges in distinguishing conspecific bacterial strains. This is especially true when dealing with low-accuracy sequencing reads such as PacBio CLR and Oxford Nanopore. While these technologies provide unequaled throughput and read length, the high error rate makes it difficult to distinguish close bacterial strains. Consequently, current de novo metagenome assembly methods excel to assemble dominant species but struggle to reconstruct low-abundance strains. In our study, we innovate by approaching strain separation as an integer linear programming (ILP) problem. We introduce a strain-separation module, strain Miner, and integrate it into an established pipeline to create strain-separated assemblies from sequencing data. Across simulated and real experiments encompassing a wide range of error rates (5-12%), our tool consistently compared favorably to the state-of-the-art in terms of assembly quality and strain reconstruction. Moreover, strainMiner substantially cuts down the computational burden of strain-level assembly compared to published software by leveraging the powerful Gurobi solver. We think the new methodological ideas presented in this paper will help democratizing strain-separated assembly. © 2024 by SCITEPRESS– Science and Technology Publications, Lda.

关键词： integer linear programming

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V-Shaped BAS: Applications on Large Portfolios Selection Problem

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COMPUTATIONAL ECONOMICS 2022年第4期60卷 1353-1373页

作者： Mourtas, Spyridon D. Katsikis, Vasilios N. Natl & Kapodistrian Univ Athens Dept Econ Div Math & Informat Sofokleous 1 St Athens 10559 Greece

The beetle antennae search (BAS) algorithm is a memetic meta-heuristic optimization algorithm capable of solving combinatorial optimization problems. In this paper, the binary version of BAS (BBAS) is modified by adding a V-shaped transfer function. In this way, we introduce the V-shaped transfer function-based binary BAS (VSBAS) algorithm, which is a more effective and efficient version of BBAS in the case of large input data. Applications using real-world data sets on a binary Markowitz-based portfolio selection (BMPS) problem validate the excellent performance of VSBAS on large input data and demonstrate that it is a marvelous alternative against other ordinary memetic meta-heuristic optimization algorithms. Note that, because the meta-heuristic algorithms compared in this paper are directly applicable only to unconstrained optimization, the penalty function method was used to keep their solutions in the feasible district. In order to support and promote the findings of this work, we have constructed a complete MATLAB package for the interested user, which is freely available through GitHub.

关键词： Beetle antennae search algorithm Meta-heuristic optimization integer linear programming Binary optimization Portfolio selection

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An integer programming formulation of the key management problem in wireless sensor networks

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OPTIMIZATION LETTERS 2020年第5期14卷 1037-1051页

作者： Xu, Guanglin Semenov, Alexander Rysz, Maciej Univ N Carolina Dept Syst Engn & Engn Management Charlotte NC USA Univ Jyvaskyla Fac Informat Technol Jyvaskyla Finland Miami Univ Dept Informat Syst & Analyt Oxford OH 45056 USA

With the advent of modern communications systems, much attention has been put on developing methods for securely transferring information between constituents of wireless sensor networks. To this effect, we introduce a mathematical programming formulation for the key management problem, which broadly serves as a mechanism for encrypting communications. In particular, an integer programming model of theq-Composite scheme is proposed and utilized to distribute keys among nodes of a network whose topology is known. Numerical experiments demonstrating the effectiveness of the proposed model are conducted using using a well-known optimization solver package. An illustrative example depicting an optimal encryption for a small-scale network is also presented.

关键词： Key management Wireless sensor networks q-Composite method integer linear programming Optimization

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Dynamic Inter-node ILP Based Multi-Scratchpad Management for Deep Learning Accelerators

Dynamic Inter-node ILP Based Multi-Scratchpad Management for...

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作者： Jang, Tajung Drexel University

学位级别：M.S., Master of Science/Master of Surgery

The landscape of deep learning compiler frameworks has evolved rapidly with the development of various tools, such as TVM, deeptools, TensorFlow, DLVM, nGraph, and Glow. These frameworks offer unique optimizations to address computation and data movement challenges in deep learning accelerators (DLAs). These approaches include graph or IR level optimizations related to intra node memory access optimizations, operator fusion, and various tiling techniques. Despite their unique approaches, these frameworks primarily concentrate on node level optimizations that focus on increasing the performance of executing a scheduled kernel operation in the graph and overlook the potential for inter-node data reuse optimizations within on-chip memory resources. OnSRAM, a scratchpad management framework build to work with deep learning compilers, addresses this gap by focusing on internode scratchpad management in DLAs. OnSRAM exploits the static graph representations of deep learning models by identifying data structures that can be pinned to on-chip memory based on their reuse rate and cost of transfer from main memory. OnSRAM has been implemented and evaluated on a single DLA that contains a monolithic scratchpad and is integrated as part of a custom deep learning compiler framework. In this work, we extend the capabilities of OnSRAM by introducing an optimal dynamic scratchpad allocation for static graph execution models using any number of scratchpads via integer linear programming (ILP) to optimize an accurate cost model of data transfers. This enhancement allows for more wholistic control over on-chip memory resources compared to the heuristic approach OnSRAM takes, providing increased flexibility and adaptability to better accommodate diverse deep learning accelerators and memory access patterns. By optimizing inter-node data movement and storage across multiple scratchpads, our approach further reduces energy consumption and latency associated with inter-node communication.

关键词： Deep learning integer linear programming Scratchpad Scratchpad management Inter-node communication

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integer programming approaches to find row-column arrangements of two-level orthogonal experimental designs

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IISE TRANSACTIONS 2020年第7期52卷 780-796页

作者： Nha Vo-Thanh Goos, Peter Schoen, Eric D. Univ Hohenheim Inst Crop Sci Stuttgart Germany Katholieke Univ Leuven Fac Biosci Engn Leuven Belgium Katholieke Univ Leuven Leuven Stat Res Ctr LSTAT Leuven Belgium Univ Antwerp Fac Business & Econ Antwerp Belgium TNO Zeist Netherlands

Design of experiments is an effective, generic methodology for problem solving as well as for improving or optimizing product design and manufacturing processes. The most commonly used experimental designs are two-level fractional factorial designs. In recent years, nonregular fractional factorial two-level experimental designs have gained much popularity compared to the traditional regular fractional factorial designs, because they offer more flexibility in terms of run size as well as the possibility to estimate partially aliased effects. For this reason, there is much interest in finding good nonregular designs, and in orthogonal blocking arrangements of these designs. In this contribution, we address the problem of finding orthogonal blocking arrangements of high-quality nonregular two-level designs in scenarios with two crossed blocking factors. We call these blocking arrangements orthogonal row-column arrangements. We propose two strategies to find row-column arrangements of given two-level orthogonal treatment designs such that the treatment factors' main effects are orthogonal to both blocking factors. The first strategy involves a sequential approach which is especially useful when one blocking factor is more important than the other. The second strategy involves a simultaneous approach for situations where both blocking factors are equally important. For the latter approach, we propose three different optimization models, so that, in total, we consider four different methods to obtain row-column arrangements. We compare the performance of the four methods by looking for good row-column arrangements of the best two-level 24-run orthogonal designs in terms of the G-aberration criterion, and apply the best of these methods to 64- and 72-run orthogonal designs.

关键词： Aliasing confounding generalized word-length pattern integer linear programming crossed blocking factors row-column design

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Integrated integer programming and decision diagram search tree with an application to the maximum independent set problem

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CONSTRAINTS 2020年第1-2期25卷 23-46页

作者： Gonzalez, Jaime E. Cire, Andre A. Lodi, Andrea Rousseau, Louis-Martin Polytech Montreal Dept Math & Ind Engn Montreal PQ Canada Univ Toronto Scarborough Dept Management Toronto ON Canada

We propose an optimization framework which integrates decision diagrams (DDs) and integer linear programming (ILP) to solve combinatorial optimization problems. The hybrid DD-ILP approach explores the solution space based on a recursive compilation of relaxed DDs and incorporates ILP calls to solve subproblems associated with DD nodes. The selection of DD nodes to be explored by ILP technology is a significant component of the approach. We show how supervised machine learning can be useful to detect, on-the-fly, a subproblem structure for ILP technology. We use the maximum independent set problem as a case study. Computational experiments show that, in presence of suitable problem structure, the integrated DD-ILP approach can exploit complementary strengths and improve upon the performance of both a stand-alone DD solver and an ILP solver in terms of solution time and number of solved instances.

关键词： Decision diagrams Integrated methods integer linear programming Hybrid optimization Supervised learning

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Planning of three-level facilities network for collection and recycling of E-waste: A MILP-based modelling approach 2nd

Planning of three-level facilities network for collection an...

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2nd International Conference on Management and Recycling of Metallurgical Wastes, MetWaste 2023

作者： Chouksey, Ankit Agrawal, Munmun Jha, Rohit Micron Technology Hyderabad India Varanasi India

The collection and recycling of E-waste are vital for the economy, the environment, and public health. From a financial perspective, planning the necessary E-waste facilities, including the collection centres and recycling centres, can be a challenging and laborious undertaking. The E-waste recycling facilities network planning problem involves three types of facilities related to different stages. Firstly, E-waste generated from households is collected at a location known as a collection point, from where it is transported to collection centres where it is sorted into several product groups, and lastly, it is sent to relevant recycling facilities. The recovered materials in recycling facilities are then forwarded to original manufacturers for reuse, while hazardous waste is dumped in landfills. The capacity and location decisions of recycling facilities are strategic and important as it involves huge capital investment, and they should be far from residential areas. Furthermore, to reduce transportation costs, these facilities should be located nearby collection centres and landfills. So, to reduce the overall E-waste recycling cost, the decision regarding the number and location of all three facilities plays an important role. In this study, the planning problem of determining the optimal number and location of collection points, collection centres, and recycling centres, as well as the flow of E-waste to these facilities, has been tackled by proposing a mixed-integer linear programming (MILP) formulation. The objective is to minimise the overall cost associated with these operations. The costs include the transportation cost and the cost of establishing all types of E-waste facilities. The application of the model has been demonstrated using a numerical example. The numerical case has been solved using GUROBI 8.0.1 optimisation solver. This study provides a framework to plan an effective and efficient network of E-waste facilities at minimum cost and lesser envir

关键词： integer linear programming

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