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IEEE International Conference on Industrial Engineering and Engineering Management (IEEM)

作者： Chen, Shin-Guang Tungnan Univ Dept Ind Management New Taipei Taiwan

ISBN: (纸本)9781509036653

Fast enumeration (FE) is a way of efficiency improvement in explicit enumeration. Since its development. in 2013, FE gains much attention in the solution of integer programming problems. An integer programming problem is a mathematical optimization or feasibility programming in which some or all of the variables are restricted to be integers. In many cases, the problems can be divided into integer linear programming problems, integer non-linear programming (INLP) problems, and mixed integer programming problems. FE is a re-arrangement of the order of constraints in its enumeration process. Such rearrangement can greatly reduce the computation complexity in its enumeration. However, different re-arrangement would result in different degree of improvement in efficiency. Therefore, an optimal re-arrangement should he developed to maximize the degree of improvement in efficiency. This paper proposes an algorithm to generate the optimal rearrangement in FE for INLP, and presents a numerical example to explain the proposed method.

关键词： integer programming explicit enumeration fast enumeration integer non-linear programming constraint re-arrangement

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QoE-Traffic optimization Through Collaborative Edge Caching in Adaptive Mobile Video Streaming

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IEEE ACCESS 2018年 6卷 52261-52276页

作者： Mehrabi, Abbas Siekkinen, Matti Yla-Jaaski, Antti Aalto Univ Dept Comp Sci FI-00076 Espoo Finland

Multi-access edge computing has been proposed as a promising approach to localize the access of mobile clients to the network edges, therefore, reducing significantly the traffic congestion on the backhaul network. Due to time-varying wireless channel condition, the video caching at the mobile edges for dynamic adaptive video streaming over HTTP (DASH) needs to be efficiently handled to alleviate the high bandwidth demand on the backhaul network and improve the quality of experience (QoE) of end users. We investigate the impact of collaborative mobile edge caching on joint QoE and backhaul data traffic by proposing the joint QoE-traffic optimization with collaborative edge caching which introduces the BFTR (backhaul/fronthaul traffic ratio) parameter adjustable by the mobile network operator. We then design a self-tuned bitrate selection algorithm with low complexity to solve the optimization problem and further propose an efficient cache replacement strategy called retention-based collaborative caching. Through simulation-based evaluations, we show a noticeable gain in the percentage of cache miss and specify some threshold for BFTR parameter after which the significant reduction in the data traffic with further improvement in average video bitrate is obtained using collaborative caching. Our findings help mobile edge system developers design an efficient collaborative caching mechanism for 5G networks.

关键词： Collaborative caching dynamic adaptive video streaming over HTTP (DASH) fairness integer non-linear programming multi-access edge computing (MEC) NP-hardness quality of experience

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Multi-objective optimization for integrated sugarcane cultivation and harvesting planning

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EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2023年第1期309卷 330-344页

作者： Aliano Filho, Angelo Oliveira, Washington A. Melo, Teresa Univ Tecnol Fed Parana Dept Matemat BR-86800020 Apucarana PR Brazil Univ Estadual Campinas Fac Ciencias Aplicadas BR-13483531 Limeira Brazil Saarland Univ Appl Sci Business Sch D-66123 Saarbrucken Germany

Sugarcane and its by-products make a relevant contribution to the world economy. In particular, the sugar-energy industry is affected by the timing of sugarcane cultivation and harvesting from which su-crose and bio-energy are produced. We address this issue by proposing a mixed-integer non-linear pro-gramming model to schedule planting and harvesting operations for different varieties of sugarcane. The decisions to be made include the choice of sugarcane varieties to be grown on a given set of plots, the periods for their cultivation, the subsequent harvesting periods, and the type of harvesting equipment. These decisions are subject to various constraints related to matching cultivation periods with harvesting periods according to the maturity cycles of the selected sugarcane varieties, the availability of harvesting machinery, the demand for sucrose and fiber, and further technical requirements. The tactical cultivation and harvesting plans to be determined account for three conflicting objectives, namely maximization of the total sucrose and fiber production, minimization of the total time devoted to harvesting, and mini-mization of the total cost of transporting the harvesting equipment. We develop a tailored exact method based on the augmented Chebyshev scalarization technique extended with a mechanism for identify-ing an initial feasible integer solution that greatly helps reduce the computational effort for obtaining Pareto-optimal solutions. Our computational study with instances that reflect the current cultivation and harvesting practices in Brazil demonstrate the effectiveness of the proposed methodology. In addition, a comparative analysis reveals the trade-offs achieved by alternative planting and harvesting schedules, thereby facilitating the decision-making process. (c) 2022 Elsevier B.V. All rights reserved.

关键词： OR in agriculture Integrated cultivation and harvesting planning Multi-objective optimization integer non-linear programming Sugar-energy industry

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Maximum probabilistic all-or-nothing paths

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EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2020年第1期283卷 279-289页

作者： Goldberg, Noam Poss, Michael Bar Ilan Univ Dept Management IL-5290002 Ramat Gan Israel Rutgers State Univ Management Sci & Informat Syst Dept Rutgers Business Sch Piscataway NJ 08854 USA Univ Montpellier LIRMM CNRS Montpellier France

We consider the problem of a maximum probabilistic all-or-nothing network path. Each arc is associated with a profit and a probability and the objective is to select a path with maximum value for the product of probabilities multiplied by the sum of arc profits. The problem can be motivated by applications including serial-system design or subcontracting of key project activities that may fail. When subcontracting such critical success activities, each must be completed on time, according to the specs, and in a satisfactory manner in order for the entire project to be deemed successful. We develop a dynamic programming (DP) method for this problem in the acyclic graph setting, under an independence assumption. Two different fully-polynomial approximation schemes are developed based on the DP formulations, one of which applies repeated rounding and scaling to the input data, while the other uses only rounding. In experiments we compare the DP approach with mixed-integer nonlinear programming (MINLP) using a branch-and-cut method, on synthetic randomly generated instances as well as realistic ones. (C) 2019 Elsevier B.V. All rights reserved.

关键词： Networks Dynamic programming integer non-linear programming FPTAS

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Profit-Maximizing Service Function Chain Embedding in NFV-Based 5G Core Networks

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IEEE TRANSACTIONS ON NETWORK SCIENCE AND ENGINEERING 2024年第6期11卷 6105-6117页

作者： Chen, Zhenke Li, He Ota, Kaoru Dong, Mianxiong Muroran Inst Technol Dept Sci & Informat Muroran 0508585 Japan

Network Function Virtualization (NFV) is a promising technology to make 5G networks more flexible and cost-efficient. With NFV, a 5G network service is implemented as several Virtual Network Functions (VNFs) that run on general machines, called a Service Function Chain (SFC). A recent survey has revealed that when multiple VNFs are colocated in the same machine, contention for shared physical resources will occur and hence degrade the throughput of a VNF and finally increase its processing delays by 50%, as compared to it runs in isolation. However, prior works fail to capture this important characteristic because they simply treat machines as a resource pool without any resource contention happening, making their approach inapplicable to the SFC embedding problem when resource contention is taken into consideration. To bridge that gap, in this paper, we study a contention-aware QoS-guaranteed SFC embedding problem and formulate it as an integer non-linear programming (INLP) under a couple of constraints. Given the formulated problem is challenging to solve due to high complexity, we propose a low-complexity approach, which can achieve a near-optimal result in a reasonable time. Numerical results reveal that the proposed approach has advantages in profit, delay, and execution time compared with other state-of-the-art approaches.

关键词： 5G mobile communication Delays Costs Quality of service Interference Heuristic algorithms Service function chaining Network function virtualization software-defined networking 5G virtual network function service function chain integer non-linear programming

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An extended cutting plane method for a class of non-convex MINLP problems

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COMPUTERS & CHEMICAL ENGINEERING 1998年第3期22卷 357-365页

作者： Westerlund, T Skrifvars, H Harjunkoski, I Porn, R Abo Akad Univ Proc Design Lab FIN-20500 Turku Finland Abo Akad Univ Dept Math FIN-20500 Turku Finland

An extended cutting plane method is introduced. The extended method can be applied in the solution of a class of non-convex MINLP (mixed-integer non-linear programming) problems, although the method was originally introduced for the solution of convex problems only. Global convergence properties of the method are given for pseudo-convex MINLP problems in the present paper and a numerical example from the paper-converting industry is finally provided to illustrate the numerical procedure. (C) 1998 Elsevier Science Ltd. All rights reserved.

关键词： optimization mixed-integer non-linear programming integer non-linear programming quasi-convex functions pseudo-convex functions extended cutting plane method

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Solving Pseudo-Convex Mixed integer Optimization Problems by Cutting Plane Techniques

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OPTIMIZATION AND ENGINEERING 2002年第3期3卷 253-280页

作者： Westerlund, Tapio Porn, Ray Abo Akad Univ Proc Design Lab FIN-20500 Turku Finland Swedish Polytech Technol & Commun FIN-65200 Vaasa Finland

In the present paper a cutting plane approach to solve mixed-integer non-linear programming (MINLP) problems, containing pseudo-convex functions, is given. It is shown how valid cutting planes for pseudo convex functions can be obtained and, furthermore, it is shown how a class of non-convex MINLP problems with a pseudo-convex objective function and pseudo-convex constraints, can be solved to global optimality with the considered cutting plane technique. Finally the numerical efficiency of the procedure, when solving some example problems, is illustrated.

关键词： optimization mixed-integer non-linear programming integer non-linear programming quasi-convex functions pseudo-convex functions non-convex MINLP problems extended cutting plane method

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A NEW APPROXIMATION FOR INVENTORY CONTROL SYSTEM WITH DECISION VARIABLE LEAD-TIME AND STOCHASTIC DEMAND

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INTERNATIONAL JOURNAL OF INDUSTRIAL ENGINEERING-THEORY APPLICATIONS AND PRACTICE 2013年第3-4期20卷 262-272页

作者： Akcan, Serap Kokangul, Ali Univ Aksaray Dept Ind Engn TR-68100 Aksaray Turkey Cukurova Univ Dept Ind Engn TR-01330 Adana Turkey

Demand for any material in a hospital depends on a random arrival rate and random length of stay in units. Therefore, the demand for any material shows stochastic characteristics that make determining the optimum level of r and Q problem more difficult. Thus, in this study, a single item inventory system for healthcare was developed using a continuous review (r, Q) policy. A simulation meta-model was constructed to obtain equations for the average on-hand inventory and average number of orders per year. Then, the equations were used to determine the optimal levels of r and Q while minimizing the total cost in an integer non-linear model. The same problem investigated in this study was also solved using OptQuest optimization software.

关键词： Healthcare systems Inventory control (r, Q) policy integer non-linear programming Simulation meta-modeling

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Different formulations for solving trim loss problems in a paper-converting mill with ILP

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COMPUTERS & CHEMICAL ENGINEERING 1996年第SUPPL.1期20卷 S121-S126页

作者： Harjunkoski, I Westerlund, T Isaksson, J Skrifvars, H ABO AKAD UNIV PROC DESIGN LABFIN-20500 TURKUFINLAND WISAPAK CORP FIN-66900 JAKOBSTADFINLAND

In the present paper, trim loss problems connected to the paper-converting industry are analyzed and solved. The objective is to produce a set of paper rolls from storage rolls such that a cost function including the minimization of the trim loss as well as the time for cutting is considered. The problem is a non-convex integer non-linear programming (INLP) problem, due to its bilinear constraints. The problem can, however, be written in an expanded linear form and can, thus, be solved as an integer linear programming (ILP) or a mixed integer linear programming (MILP) problem. The linear formulation is attractive from the point of view of formality. One drawback of linear formulations is the increased number of variables and constraints they give rise to. It is, though, of interest to compare different ways of describing the problem as an ILP/MILP problem. There has previously been some academic interest in solving trim loss problems as linear programming problems. In this paper, we will present a general INLP formulation, some ways to formulate and solve it as an ILP or MILP problem and compare the efficiency of these different approaches. The examples considered are taken from real daily trim optimization problems encountered at a Finnish paper-converting mill with a capacity of 100,000 tons/year.

关键词： optimization integer linear programming integer non-linear programming trim loss problems scheduling problems

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An Adaptive Clustering Approach Based on Minimum Travel Route Planning for Wireless Sensor Networks with a Mobile Sink

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SENSORS 2017年第5期17卷 964-964页

作者： Tang, Jiqiang Yang, Wu Zhu, Lingyun Wang, Dong Feng, Xin Chongqing Univ Technol Coll Comp Sci & Engn Chongqing 400054 Peoples R China

In recent years, Wireless Sensor Networks with a Mobile Sink (WSN-MS) have been an active research topic due to the widespread use of mobile devices. However, how to get the balance between data delivery latency and energy consumption becomes a key issue of WSN-MS. In this paper, we study the clustering approach by jointly considering the Route planning for mobile sink and Clustering Problem (RCP) for static sensor nodes. We solve the RCP problem by using the minimum travel route clustering approach, which applies the minimum travel route of the mobile sink to guide the clustering process. We formulate the RCP problem as an integer non-linear programming (INLP) problem to shorten the travel route of the mobile sink under three constraints: the communication hops constraint, the travel route constraint and the loop avoidance constraint. We then propose an Imprecise Induction Algorithm (IIA) based on the property that the solution with a small hop count is more feasible than that with a large hop count. The IIA algorithm includes three processes: initializing travel route planning with a Traveling Salesman Problem (TSP) algorithm, transforming the cluster head to a cluster member and transforming the cluster member to a cluster head. Extensive experimental results show that the IIA algorithm could automatically adjust cluster heads according to the maximum hops parameter and plan a shorter travel route for the mobile sink. Compared with the Shortest Path Tree-based Data-Gathering Algorithm (SPT-DGA), the IIA algorithm has the characteristics of shorter route length, smaller cluster head count and faster convergence rate.

关键词： hierarchy wireless sensor network with a mobile sink travel route planning cluster multi-hop communication integer non-linear programming

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