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Optimization modeling modeling of multi-skilled resources in prefabrication: Theorizing cost analysis of process integration in off-site construction

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AUTOMATION IN CONSTRUCTION 2018年 95卷 1-9页

作者： Arashpour, Mehrdad Kamat, Vineet Bai, Yu Wakefield, Ron Abbasi, Babak Monash Univ Dept Civil Engn 23 Coll Walk Clayton Vic 3800 Australia Univ Michigan Dept Civil & Environm Engn 1221 Beal Ave Ann Arbor MI 48109 USA RMIT Univ Sch Property Construct & Project Management 360 Swanston St Melbourne Vic 3000 Australia RMIT Univ Sch Business IT & Logist 360 Swanston St Melbourne Vic 3000 Australia

In advanced manufacturing of building elements, process integration and utilization of multi-skilled resources enhance the flexibility of production networks against variations in demand and resource availability. This research study aims to incorporate the required cost and time for crass-training multi-skilled resources into resource planning computations. Towards this aim, minimizing the cost of utilizing multi-skilled resources in offsite construction is formulated using integer and probabilistic optimization models. Production data of two prefabrication networks in Brisbane and Melbourne, Australia are used to derive computational results and validate models. The main contribution of this research study is to analyze the costeffectiveness of deploying multi-skilled resources with the aim of improving production flexibility. The modeling methodology and findings are of practical use to off-site manufacturers that experience variations in production demand and resource availability.

关键词： Agile workforce Cost modeling Cross-training resources integer and linear programming Performance measures Prefabricated building elements Project management Resource planning theory Skill-chaining Workflow variance

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Approximation algorithm for the group Steiner network problem

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NETWORKS 2007年第2期49卷 160-167页

作者： Penn, Michal Rozenfeld, Stas Technion Israel Inst Technol Fac Ind Engn & Management IL-32000 Haifa Israel

In this article we study the group Steiner network problem, which is defined in the following way. Given a graph G = (V,E), a partition of its vertices into K groups and connectivity requirements between the different groups, the aim is to find simultaneously a set of representatives, one for each group, and a minimum cost connected subgraph that satisfies the connectivity requirements between the groups (representatives). This problem is a generalization of the Steiner network problem and the group Steiner tree problem, two known NP-complete problems. We present an approximation algorithm for a special case of the group Steiner network problem with an approximation ratio of min {2(1 + 2x),2I}, where I is the cardinality of the largest-group and x is a parameter that depends on the cost function. (c) 2006 Wiley Periodicals, Inc.

关键词： group Steiner network approximation algorithm integer and linear programming

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WEIGHTED FRACTIONAL AND INTEGRAL KAPPA-MATCHING IN HYPERGRAPHS

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DISCRETE APPLIED MATHEMATICS 1995年第2-3期57卷 255-269页

作者： SRIVASTAV, A STANGIER, P UNIV COLOGNE INST INFORMATD-50969 COLOGNEGERMANY

We consider the problem of finding polynomial-time approximations of maximal weighted k-matchings in a hypergraph and investigate the relationship between the integral and fractional maxima of the corresponding 0-1 integer linear program and its LP-relaxation. We extend results of Raghavan, who gave a deterministic approximation algorithm for unweighted k-matching, to the weighted case and compare the so obtained lower bound for the ratio of the integer and fractional maximum with a lower bound of Aharoni et al. (1985) and Alon et al. (1992).

关键词： HYPERGRAPH MATCHING integer and linear programming RANDOMIZED ALGORITHM DERANDOMIZATION

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Customer segmentation, allocation planning and order promising in make-to-stock production

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OR SPECTRUM 2009年第1期31卷 229-256页

作者： Meyr, Herbert Tech Univ Darmstadt Chair Prod & Supply Chain Management D-64289 Darmstadt Germany

Modern advanced planning systems offer the technical prerequisites for an allocation of "available-to-promise" (ATP) quantities-i.e. not yet reserved stock and planned production quantities-to different customer segments and for a real time promising of incoming customer orders (ATP consumption) respecting allocated quota. The basic idea of ATP allocation is to increase revenues by means of customer segmentation, as it has successfully been practiced in the airline industry. However, as far as manufacturing industries and make-to-stock production are concerned, it is unclear, whether, when, why and how much benefits actually arise. Using practical data of the lighting industry as an example, this paper reveals such potential benefits. Furthermore, it shows how the current practice of rule-based allocation and consumption can be improved by means of up-to-date demand information and changed customer segmentation. Deterministic linear programming models for ATP allocation and ATP consumption are proposed. Their application is tested in simulation runs using the lighting data. The results are compared with conventional real time order promising with(out) customer segmentation and with batch assignment of customer orders. This research shows that-also in make-to-stock manufacturing industries-customer segmentation can indeed improve profits substantially if customer heterogeneity is high enough and reliable information about ATP supply and customer demand is available. Surprisingly, the choice of an appropriate number of priority classes appears more important than the selection of the ATP consumption policy or the clustering method to be applied.

关键词： Available-to-Promise (ATP) Advanced planning systems Clustering integer and linear programming Order promising

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A LARGE MIXED integer PRODUCTION AND DISTRIBUTION PROGRAM

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EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 1987年第2期28卷 207-217页

作者： DURAN, F BAVARIA SA CARRERA 13 2801BOGOTACOLOMBIA

A decomposition algorithm for a production and distribution problem allows finding a very good suboptimal solution for an 85000 variable model with 2600 0-1 variables. A global reoptimization process of the continuous part improves the final solution. Annual savings over 3.7% of variable costs and a reasonable CPU time are obtained. A user-oriented program (generation, solution and report) is developed. [ABSTRACT FROM AUTHOR]

关键词： Distribution integer and linear programming practice production

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Point Guards and Point Clouds: Solving General Art Gallery Problems

Point Guards and Point Clouds: Solving General Art Gallery P...

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29th Annual Symposium on Computational Geometry (SoCG)

作者： Borrmann, Dorit de Rezende, Pedro J. de Souza, Cid C. Fekete, Sandor P. Friedrichs, Stephan Kroeller, Alexander Nuechter, Andreas Schmidt, Christiane Tozoni, Davi C. Jacobs Univ Bremen Automat Grp Bremen Germany Univ Estadual Campinas Inst Comp Campinas SP Brazil TU Braunschweig Comp Sci Braunschweig Germany

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A Routing and Placement Scheme for Network Function Virtualization 40

A Routing and Placement Scheme for Network Function Virtuali...

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40th International Conference on Telecommunications and Signal Processing (TSP)

作者： Crichigno, Jorge Oliveira, Diogo Pourvali, Mahsa Ghani, Nasir Torres, David Univ South Carolina Dept Integrated Informat Technol Columbia SC 29208 USA Northern New Mexico Coll Coll Engn & Technol Espanola NM 87532 USA Univ S Florida Dept Elect Engn Tampa FL 33620 USA

ISBN: (纸本)9781509039821

Network Function Virtualization (NFV) and Software-Defined Networking (SDN) are two paradigms that have attracted much attention in the networking field. The first permits the implementation of Network Functions (NFs) on commodity servers located in datacenters. The second facilitates the management and routing of network flows by controllers. While recent work has mostly explored the use of NFV and SDN with the goal of minimizing the resources to satisfy a set of requested NFs, the application of these two paradigms has not been studied in scenarios where resources are limited. Those scenarios are typical when parts of the network or datacenters fail. Hence, this paper presents an optimization scheme based on integer linear programming (ILP) for the joint routing and placement of virtual NFs problem. Given a set of requests, each consisting of NFs and end points of the traffic flow, the objective of the scheme is the maximization of the number of NFs satisfied. At the same, the scheme minimizes both the routing and infrastructure costs to satisfy the requests. While numerical results demonstrate that the proposed ILP can be used in small/medium-sized networks, the paper also presents a low-complexity greedy heuristic approach for large networks.

关键词： Greedy algorithm integer and linear programming Network Function Virtualization (NFV)

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Learning with Structured Sparsity: From Discrete to Convex and Back

Learning with Structured Sparsity: From Discrete to Convex a...

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作者： Marwa EL HALABI ECOLE POLYTECHNIQUE FEDERALE DE LAUSANNE

学位级别：博士

In modern-data analysis applications, the abundance of data makes extracting meaningful infor- mation from it challenging, in terms of computation, storage, and interpretability. In this setting, exploiting sparsity in data has been essential to the development of scalable methods to problems in machine learning, statistics and signal processing. However, in various applications, the input variables exhibit structure beyond simple sparsity. This motivated the introduction of structured sparsity models, which capture such sophisticated structures, leading to significant performance gains and better interpretability. Structured sparsity approaches have been successfully applied in a variety of domains including computer vision, text and audio processing, medical imaging, and bioinformatics. The goal of this thesis is to improve on these methods and expand their success to a wider range of applications. We thus develop novel methods to incorporate general structure a priori in learning problems, which balance computational and statistical efficiency trade-offs. To achieve this, our results bring together tools from discrete and convex optimization. Applying structured sparsity approaches in general is challenging because structures encountered in practice are naturally combinatorial. An effective approach to circumvent this computational challenge is to employ continuous convex relaxations. We thus start by introducing a new class of structured sparsity models, able to capture a large range of structures, which admit tight convex relaxations amenable to efficient optimization. We then present an in-depth study of the geometric and statistical properties of convex relaxations of general combinatorial structures. In particular, we characterize which structure is lost by imposing convexity and which is preserved. We then focus on the optimization of the convex composite problems that result from the convex relaxations of structured sparsity models. We develop efficient al

关键词： Structured sparsity high-dimensional learning convex relaxations convex composite minimization integer and linear programming submodularity

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Near-Regular Structure Discovery Using linear programming

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ACM TRANSACTIONS ON GRAPHICS 2014年第3期33卷 23-1-23-17页

作者： Huang, Qixing Guibas, Leonidas J. Mitra, Niloy J. Stanford Univ Stanford CA 94305 USA UCL Dept Comp Sci London England

Near-regular structures are common in manmade and natural objects. Algorithmic detection of such regularity greatly facilitates our understanding of shape structures, leads to compact encoding of input geometries, and enables efficient generation and manipulation of complex patterns on both acquired and synthesized objects. Such regularity manifests itself both in the repetition of certain geometric elements, as well as in the structured arrangement of the elements. We cast the regularity detection problem as an optimization and efficiently solve it using linear programming techniques. Our optimization has a discrete aspect, that is, the connectivity relationships among the elements, as well as a continuous aspect, namely the locations of the elements of interest. Both these aspects are captured by our near-regular structure extraction framework, which alternates between discrete and continuous optimizations. We demonstrate the effectiveness of our framework on a variety of problems including near-regular structure extraction, structure-preserving pattern manipulation, and markerless correspondence detection. Robustness results with respect to geometric and topological noise are presented on synthesized, real-world, and also benchmark datasets.

关键词： Algorithms Experimentation Theory Intrinsic near-regular structure integer and linear programming pattern manipulation markerless correspondence

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Point guards and point clouds: solving general art gallery problems 13

Point guards and point clouds: solving general art gallery p...

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Proceedings of the twenty-ninth annual symposium on Computational geometry

作者： Dorit Borrmann Pedro J. de Rezende Cid C. de Souza Sándor P. Fekete Stephan Friedrichs Alexander Kröller Andreas Nüchter Christiane Schmidt Davi C. Tozoni Jacobs University Bremen Bremen Germany University of Campinas Campinas Brazil TU Braunschweig Braunschweig Germany

ISBN: (纸本)9781450320313

In this video, we illustrate how one of the classical areas of computational geometry has gained in practical relevance, which in turn gives rise to new, fascinating geometric problems. In particular, we demonstrate how the robot platform IRMA3D can produce high-resolution, virtual 3D environments, based on a limited number of laser scans. Computing an optimal set of scans amounts to solving an instance of the Art Gallery Problem (AGP): Place a minimum number of stationary guards in a polygonal region P, such that all points in P are guarded.

关键词： mobile robots exact optimization art gallery problem integer and linear programming geometric optimization three-dimensional laser scanning

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