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检索条件"任意字段=13th International Conference on Integer Programming and Combinatorial Optimization"

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A dynamical constraint-generating algorithm for the Single-Vehicle Cyclic Inventory-Routing Problem

A dynamical constraint-generating algorithm for the Single-V...

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16th IFAC Symposium on Information Control Problems in Manufacturing (INCOM)

作者： Lefever, Wouter Aghezzaf, El-Houssaine Hadj-Hamou, Khaled Univ Ghent Dept Ind Syst Engn & Prod Design Technol Pk 903 B-9052 Zwijnaarde Belgium Univ Lyon INSA Lyon DISP F-69621 Villeurbanne France

the Single-Vehicle Cyclic Inventory-Routing Problem (SVCIRP) is a variant of the Inventory-Routing Problem (IRP) in which the replenishment decisions of a recurring distribution plan are optimized. In this paper, we investigate the current formulation of the SVCIRP and propose a number of improvements for it. First, we introduce a new binary variable in the model to distinguish tours in which only one retailer is visited. Additionally, we formulate three new sets of valid inequalities. Because one of the sets contains an exponential number of inequalities, we develop a procedure to insert only the violated inequalities. We present an algorithm, based on this procedure, to solve the SVCIRP effectively. Our computational results show that our algorithm outperforms the other exact methods in literature. We obtain 25 new best bounds and we find 13 improved solutions. (C) 2018, IFAC (international Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.

关键词： combinatorial mathematics Mathematical models integer programming Convex optimization Bounding method

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Solving the Steiner Tree Problem with Revenues, Budget and Hop Constraints to optimality

Solving the Steiner Tree Problem with Revenues, Budget and H...

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international conference on Modeling, Simulation and Applied optimization

作者： Safa Bhar Layeb Ines Hajri Mohamed Haouari Combinatorial Optimization Research Group - ROI Ecole Polytechnique de Tunisie Department of Industrial Engineering Ozyegin University

ISBN: (纸本)9781467358125

We investigate the Steiner tree problem with revenues, budget and hop constraints (STPRBH) on graph, which is a generalization of the well-known Steiner tree problem. Given a root node, edge costs, nodes revenues, as well as a preset budget and hop, the STPRBH seeks to find a subtree that includes the root node and maximizes the sum of the total edge revenues respecting the budget and hop constraints. these constraints impose limits on the total cost of the network and the number of edges between any vertex and the root. Not surprisingly, the STPRBH is NP-hard. For this challenging network design problem that arises in telecommunication settings and multicast routing, we present several polynomial size formulations. We propose an enhanced formulation based on the classical work of Miller, Tucker, and Zemlin by using additional set of variables representing the rank-order of visiting the nodes. Also, we investigate a new formulation for the STPRBH by tailoring a partial rank-1 of the Reformulation-Linearization Technique. Extensive results are exhibited using a set of benchmark instances to compare the proposed formulations by using a general purpose MIP solver.

关键词： Steiner tree Mixed integer programming MTZ subtour elimination constraints Reformulation-Linearization technique

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optimization of production system with environmental consideration: the effect of worker learning in a metallurgy factory

Optimization of production system with environmental conside...

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international conference on Logistics (LOGISTIQUA)

作者： Djazia Nadjat Sekkal Fayçal Belkaid Manufacturing Engineering Laboratory of Tlemcen University of Tlemcen Tlemcen Algeria

ISBN: (数字)9781728198811

ISBN: (纸本)9781728198828

Over the last few years, energy consumption and carbon emissions have been the subject of a great deal of attention, due to the ever-increasing climate change and diminishing of fossil energy resources. In this context, this article aims to minimize the maximum completion time (makespan) by taking into account environmental aspects in a production system. In particular, we consider a flow shop group scheduling problem with sequence-dependent setup times, learning effect related to the ability of each operator as well as machine speeds and the various carbon emissions associated with them, inspired by a real case study of the manufacture of forged connecting rods in a metallurgy factory. the objective is to determine both an optimal scheduling of the groups and the jobs within the groups in order to minimize the makespan by restricting the carbon emissions of the system. A mixed integer linear programming model is formulated, the computational results are also presented and discussed through the different scenarios.

关键词： Production systems Job shop scheduling Optimal scheduling Carbon dioxide Simulated annealing Minimization Production facilities

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Profit-driven optimization of Server Deployment and Service Placement in Multi-User Mobile Edge Computing

Profit-driven Optimization of Server Deployment and Service ...

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international conference on Parallel and Distributed Systems (ICPADS)

作者： Juan Fang Shen Wu Shuaibing Lu Faculty of Information Technology Beijing University of Technology Beijing China

Edge computing has emerged as a promising paradigm to fulfill the escalating demands of latency-sensitive and computationally intensive applications. In this context, efficient server deployment and service placement have become imperative to optimize performance and increase platform profit. In this paper, we investigate the problem of server deployment and service placement in a multi-user scenario, aiming to enhance the profit of Mobile Network Operators (MNOs) while considering constraints related to distance thresholds, resource limitations, and connectivity requirements. then, we propose a novel two-stage method to decouple the problem, breaking down server deployment and service placement into two distinct yet interconnected stages. In stage I, the server deployment is formulated as a combinatorial optimization problem within the framework of a Markov Decision Process (MDP), where the state space, action space, and penalty function are defined to effectively model the issue. We propose the SDQ algorithm to establish a relatively stable server deployment strategy. In stage II, the service placement is formulated as a constrained integer linear programming problem. We propose the SPIB-TDB algorithm to optimize service placement. Extensive experimentation validates the exceptional performance of our proposed algorithms in enhancing the profit of MNOs.

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Mining statistical information of frequent fault-tolerant patterns in transactional databases

Mining statistical information of frequent fault-tolerant pa...

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7th IEEE international conference on Data Mining (ICDM 2007)

作者： Ardian Kristanto Poernomo Vivekanand Gopalkrishnan Nanyang Technological University Singapore

Constraints applied on classic frequent patterns are too strict and may cause interesting patterns to be missed. Hence, researchers have proposed to mine a more relaxed version of frequent patterns, where transactions are allowed to miss some items in the itemset they support. Patterns exhibiting such "faults" are called frequent fault-tolerant patterns (FFT-patterns) if they are significant in number. In this paper, the term "pattern" is distinguished from "item-set" as referring to a pair (tidset x itemset). Unlike classical frequent patterns, the number of FFT-patterns grows exponentially not only with the number of items, but also with the number of transactions. Since the latter may reach millions, mining FFT-patterns by enumerating them becomes infeasible. Hence, the challenge is to represent FFT-patterns concisely without losing any useful information. To address this, we draw on the observation that, in transactional databases, the transactions themselves are not important from the data mining point-of-view;i.e. researchers are interested in finding itemsets contained in lots of transactions, rather than in the transactions per se. therefore, we propose to mine only the frequent itemsets along with the statistical information of the supporting transaction sets, rather than enumerate entire FFT-patterns. then we present our approach - the BIAS framework, consisting of Backtracking algorithm, integer Linear programming (ILP) constraints, and aggregation statistics to solve this problem. Algorithms under this framework not only increase the efficiency of the FFT-patterns mining process by more than an order of magnitude, but also provide a more comprehensive analysis of FFT-Patterns.

关键词： Fault tolerance Transaction databases Itemsets Data mining Statistics integer linear programming Pattern analysis Algorithm design and analysis combinatorial mathematics Constraint optimization

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Joint Dynamic User Pairing, Computation Offloading and Power Control for NOMA-based MEC System

Joint Dynamic User Pairing, Computation Offloading and Power...

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international conference on Wireless Communications and Signal Processing (WCSP)

作者： Jingui Li Fan Wu Ke Zhang Supeng Leng School of Information and Communication Engineering University of Electronic and Science Technology of China Chengdu China

To tackle the massive access and different computation offloading requirements of IoT devices in 5G MEC system, Dynamic User Pairing NOMA-based offloading is considered in this paper. An overall energy consumption minimization framework is established by joint optimizing user pairing, of-floading decision and uplink power control under the time and maximum multiplexing number of user constraints. Due to the combinatorial nature of the formulated mixed integer non-linear programming problem, we adapt two-phase approach to solve the challenging problem. First, a low-complexity heuristic algorithm is designed to solve the user pairing problem. After we get the sub-optimal user pairing scheme, the original problem is proved to be a convex problem, we then get the optimal offloading decision and transmission power of devices. Numerical results show that the proposed DUP NOMA-based offloading scheme can significantly improve system performance in terms of energy consumption comparing to OMA and Fixed User Pairing NOMA based offloading.

关键词： NOMA Energy consumption Task analysis Resource management Servers Schedules optimization

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Resource optimization and Delay-aware Virtual Network Function Placement for Mapping SFC Requests in NFV-enabled Networks

Resource Optimization and Delay-aware Virtual Network Functi...

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IEEE international conference on Cloud Computing, CLOUD

作者： Yi Yue Bo Cheng Xuan Liu State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications Beijing China

ISBN: (数字)9781728187808

ISBN: (纸本)9781728187815

Network Function Virtualization (NFV) enables cloud service providers (CSPs) to flexibly place their network functions on common off-the-shelf servers in the form of virtual network functions (VNF), without incurring costly capital and operating expenses (CAPEX/OPEX). In the NFV-enabled network, service function chains (SFCs) are responsible for accomplishing users' service requests by steering traffic through a set of VNFs in a specified order. therefore, it is an important but intractable issue for CSPs to devise an optimal VNF placement scheme to enhance network performance and profits. In this paper, we focus on the VNF placement problem for mapping SFC requests (SFCRs) in NFV-enabled networks, considering the delay requirement of SFCRs. To improve resource utilization, we consider the basic resource overheads and sharability of VNF instances. then we formulate the problem as an integer linear programming (ILP) model, with the purpose of total resource consumption minimization. Afterward, the novel SFCR mapping algorithm (SMA) and VNF request adjustment algorithm (VAA) are proposed to map SFCRs and optimize the placement of VNF requests. Simulation results show that our approach is near-optimal in terms of node resource consumption. Besides, it provides higher performance in terms of node resource consumption, average VNF utilization and the number of activated servers compared with the benchmarks.

关键词： Cloud computing Benchmark testing Network function virtualization Delays Servers Resource management optimization

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Realtime Gray-Box Algorithm Configuration 16th

Realtime Gray-Box Algorithm Configuration

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16th international conference on Learning and Intelligent optimization, LION 16 2022

作者： Weiss, Dimitri Tierney, Kevin Decision and Operation Technologies Group Bielefeld University Bielefeld Germany

ISBN: (纸本)9783031248658

A solver’s runtime and the quality of the solutions it generates are strongly influenced by its parameter settings. Finding good parameter configurations is a formidable challenge, even for fixed problem instance distributions. However, when the instance distribution can change over time, a once effective configuration may no longer provide adequate performance. Realtime algorithm configuration (RAC) offers assistance in finding high-quality configurations for such distributions by automatically adjusting the configurations it recommends based on instances seen so far. Existing RAC methods treat the solver to be configured as a black box, meaning the solver is given a configuration as input, and it outputs either a solution or runtime as an objective function for the configurator. However, analyzing intermediate output from the solver can enable configurators to avoid wasting time on poorly performing configurations. To this end, we propose a gray-box approach that utilizes intermediate output during evaluation and implement it within *** pairwise comparisons to determine whether ongoing evaluations can be terminated to free resources. We compare our realtime gray-box configurator to a black-box equivalent on several experimental settings and show that our approach reduces the total solving time in several scenarios.

关键词： integer programming

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Surrogate-Assisted Hybrid Metaheuristic for Mixed-Variable 3-D Deployment optimization of Directional Sensor Networks

Surrogate-Assisted Hybrid Metaheuristic for Mixed-Variable 3...

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Data-driven optimization of Complex Systems (DOCS), international conference on

作者： Yuntian Zhang Chen Chen Tongyu Wu Changhao Miao Shuxin Ding School of Automation Beijing Institute of Technology Beijing China National Key Lab of Autonomous Intelligent Unmanned Systems Beijing China Signal and Communication Research Institute China Academy of Railway Sciences Corporation Limited Beijing China Traffic Management Laboratory for High-Speed Railway National Engineering Research Center of System Technology for High-Speed Railway and Urban Rail Transit Beijing China

A major concern in designing sensor networks is the deployment problem. However, establishing an efficient algorithm for the real-world deployment problem is challenging due to three issues, which are 1) the realistic mixed-integer nonlinear programming problem (MINLP) with mixed-variable; 2) the combinatorial subset selection problem; and 3) the expensive computational cost for fitness evaluation in the 3-D coverage problem. therefore, this paper addresses these challenges and proposes a surrogate-assisted hybrid metaheuristic for mixed-variable 3-D deployment optimization of directional sensor networks (DSNs). First, an MINLP with flexible coordinate transformation technique and an efficient mixed-variable encoding scheme are introduced to model and represent the problem. We propose hybrid metaheuristic which applies two reproduction methods respectively for discrete and continuous variables. Second, we design sparse population-based incremental learning (s-PBIL) to handle inherent subset selection problem. s-PBIL could accurately learn the required information, and automatically learn a sparse distribution. third, a mixed-variable surrogate with unifying space under Bayesian model management is incorporated to reduce the expensive computational cost. Experiment results on real-world deployment scenarios scaling from small-size to large-size show the effectiveness of the proposed algorithm.

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Adaptive embedded systems: New composed technical solutions for feasible low-power and real-time flexible OS tasks

Adaptive embedded systems: New composed technical solutions ...

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international conference on Informatics in Control, Automation and Robotics (ICINCO)

作者： Hamza Chniter Mohamed Khalgui Fethi Jarray INSAT Institute University of Carthage Carthage Tunisia ISI Institute Mednine Tunisia FST faculty University of Elmanar Elmanar Tunisia Laboratoire CEDRIC CNAM France

the paper deals with low-power adaptive scheduling of synchronous and flexible real-time OS tasks. A software reconfiguration scenario is assumed to be any run-time operation allowing the addition-removal-update of OS tasks to adapt the system to its environment under well-defined conditions. the problem is that any reconfiguration can push the system to an unfeasible behavior where temporal properties are violated or the energy consumption is possibly high and unacceptable. A task in the system can change its characteristics at any time when a reconfiguration scenario is applied, it can also be stopped or replaced by another one. the difficulty is how to find the new temporal parameters of the systems tasks after any reconfiguration. We use a DVS processor which is with a variable speed to support run-time solutions that re-obtain the system's feasibility. the challenge is how to compute the best combinations between available processor speeds for a good compromise between execution time and energy consumption. We propose a combinatorial optimization method based on integer programming and heuristics. We propose also a solution when the available speeds do not allow the feasibility of the system. Both approaches include a mechanism to adjust the deadlines of tasks to satisfy the feasibility conditions and overcome the problem of rejected tasks. this mechanism makes the scheduling more flexible and able to react in accordance with its environment.

关键词： Real-time systems Energy consumption Embedded systems Linear programming Processor scheduling Time factors Computational modeling

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