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  • Institute for Operations Research and the Management Sciences (INFORMS)  (6)
  • Mathematics  (6)
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  • Institute for Operations Research and the Management Sciences (INFORMS)  (6)
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  • Mathematics  (6)
RVK
  • 1
    Online Resource
    Online Resource
    On the Undirected Rural Postman Problem: Tight Bounds Based on a New Formulation
    Institute for Operations Research and the Management Sciences (INFORMS) ; 2003
    In:  Operations Research Vol. 51, No. 2 ( 2003-04), p. 281-291
    Details
    In: Operations Research, Institute for Operations Research and the Management Sciences (INFORMS), Vol. 51, No. 2 ( 2003-04), p. 281-291
    Abstract: The Rural Postman Problem (RPP) is a classic “edge-routing” problem. A mathematical programming formulation of the RPP that differs fundamentally from those in the literature was introduced, but not tested computationally, by Garfinkel and Webb (1999). A rudimentary algorithm that yields lower bounds via cutting planes and upper bounds via heuristics is developed and tested for a variation of that formulation. Computational results are encouraging, especially in terms of the relatively small number of added inequalities needed to get good lower bounds, and the fact that the vast majority of these have efficient, exact separation procedures. Note that a first algorithm based on this new formulation is computationally competitive, allowing the possibility of far more efficient and complex future realizations.
    Type of Medium: Online Resource
    ISSN: 0030-364X , 1526-5463
    URL: Article
    DOI: 10.1287/opre.51.2.281.12790
    RVK:
    SA 7410
    Language: English
    Publisher: Institute for Operations Research and the Management Sciences (INFORMS)
    Publication Date: 2003
    detail.hit.zdb_id: 2019440-7
    detail.hit.zdb_id: 123389-0
    SSG: 3,2
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  • 2
    Online Resource
    Online Resource
    Stochastic Power Generation Unit Commitment in Electricity Markets: A Novel Formulation and a Comparison of Solution Methods
    Institute for Operations Research and the Management Sciences (INFORMS) ; 2009
    In:  Operations Research Vol. 57, No. 1 ( 2009-02), p. 32-46
    Details
    In: Operations Research, Institute for Operations Research and the Management Sciences (INFORMS), Vol. 57, No. 1 ( 2009-02), p. 32-46
    Abstract: We propose a stochastic unit commitment model for a power generation company that takes part in an electricity spot market. The relevant feature of this model is its detailed representation of the spot market during a whole week, including seven day-ahead market sessions and the corresponding adjustment market sessions. The adjustment market sessions can be seen as an hour-ahead market mechanism. This representation takes into account the influence that the company's decisions exert on the market-clearing price by means of a residual demand curve for each market session. We introduce uncertainty in the form of several possible spot market outcomes for each day, which leads to a weekly scenario tree. The model also represents in detail the operation of the company's generation units. The model leads to large-scale mixed linear-integer problems that are hard to solve with commercial optimizers. This suggests the use of alternative solution methods. We test four solution approaches with a realistic numerical example in the context of the Spanish electricity spot market. The first is a direct solution with a commercial optimizer, which illustrates the mentioned limitations. The second is a standard Lagrangean relaxation algorithm. The third and fourth methods are two original variants of Benders decomposition for multistage stochastic integer programs. The first Benders decomposition algorithm builds approximations for the recourse function relaxing the integrality constraints of the subproblems. The second variant strengthens these cuts by performing one iteration of the Lagrangean of each subproblem. We analyze the advantages of these four methods and compare the results.
    Type of Medium: Online Resource
    ISSN: 0030-364X , 1526-5463
    URL: Article
    DOI: 10.1287/opre.1080.0593
    RVK:
    SA 7410
    Language: English
    Publisher: Institute for Operations Research and the Management Sciences (INFORMS)
    Publication Date: 2009
    detail.hit.zdb_id: 2019440-7
    detail.hit.zdb_id: 123389-0
    SSG: 3,2
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  • 3
    Online Resource
    Online Resource
    Hub Location as the Minimization of a Supermodular Set Function
    Institute for Operations Research and the Management Sciences (INFORMS) ; 2014
    In:  Operations Research Vol. 62, No. 3 ( 2014-06), p. 557-570
    Details
    In: Operations Research, Institute for Operations Research and the Management Sciences (INFORMS), Vol. 62, No. 3 ( 2014-06), p. 557-570
    Abstract: This paper highlights how a general class of hub location problems can be modeled as the minimization of a real-valued supermodular set function. Well-known problems such as uncapacitated hub location, p-hub median, and hub arc location, among others, are shown to be particular cases of this class. Two integer programming formulations are introduced and compared. One uses path-based variables, frequently employed in hub location, whereas the other exploits properties of supermodular functions. In addition, several worst case bounds for a greedy and a local improvement heuristic are obtained for the general class and for some particular cases in which sharper bounds can be devised. Computational experiments are performed to compare both formulations when used with a general purpose solver. Computational results obtained on benchmark instances confirm the superiority of the supermodular formulation.
    Type of Medium: Online Resource
    ISSN: 0030-364X , 1526-5463
    URL: Article
    DOI: 10.1287/opre.2014.1263
    RVK:
    SA 7410
    Language: English
    Publisher: Institute for Operations Research and the Management Sciences (INFORMS)
    Publication Date: 2014
    detail.hit.zdb_id: 2019440-7
    detail.hit.zdb_id: 123389-0
    SSG: 3,2
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  • 4
    Online Resource
    Online Resource
    A Large-Scale Optimization Model for Replicating Portfolios in the Life Insurance Industry
    Institute for Operations Research and the Management Sciences (INFORMS) ; 2021
    In:  Operations Research Vol. 69, No. 4 ( 2021-07), p. 1134-1157
    Details
    In: Operations Research, Institute for Operations Research and the Management Sciences (INFORMS), Vol. 69, No. 4 ( 2021-07), p. 1134-1157
    Abstract: Replicating portfolios have emerged as an important tool in the life insurance industry, used for the valuation of companies’ liabilities. This paper describes the replicating portfolio (RP) model used to approximate life insurance liabilities in a large global insurance company. We describe the challenges presented by the latest solvency regimes in Europe and how the RP model enables this company to comply with the Swiss Solvency Test. The model minimizes the L 1 error between the discounted life insurance liability cash flows and the discounted RP cash flows over a multiperiod time horizon for a broad range of different future economic scenarios. A numerical application of the RP model to empirical data sets demonstrates that the model delivers RPs that match the liabilities and perform well for economic capital calculations.
    Type of Medium: Online Resource
    ISSN: 0030-364X , 1526-5463
    URL: Article
    DOI: 10.1287/opre.2020.2098
    RVK:
    SA 7410
    Language: English
    Publisher: Institute for Operations Research and the Management Sciences (INFORMS)
    Publication Date: 2021
    detail.hit.zdb_id: 2019440-7
    detail.hit.zdb_id: 123389-0
    SSG: 3,2
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  • 5
    Online Resource
    Online Resource
    Mosaicking of Aerial Photographic Maps Via Seams Defined by Bottleneck Shortest Paths
    Institute for Operations Research and the Management Sciences (INFORMS) ; 1998
    In:  Operations Research Vol. 46, No. 3 ( 1998-06), p. 293-304
    Details
    In: Operations Research, Institute for Operations Research and the Management Sciences (INFORMS), Vol. 46, No. 3 ( 1998-06), p. 293-304
    Abstract: The Cartographic Institute of Catalonia (ICC) produces commercial aerial photographic maps of locations in Europe and South America. These maps are often so large that it is necessary to produce one map from two or more photographs, which are combined two at a time in a process called mosaicking. The objective is to make the final map appear to be the product of a single photograph by producing a seam that is invisible even to an expert cartographer. The problem and a variation are modeled via bottleneck shortest paths and cycles. Optimization algorithms are developed for both, and the first has been implemented with demonstrable impact on the company. The second represents a new class of constrained shortest cycle problems.
    Type of Medium: Online Resource
    ISSN: 0030-364X , 1526-5463
    URL: Article
    DOI: 10.1287/opre.46.3.293
    RVK:
    SA 7410
    Language: English
    Publisher: Institute for Operations Research and the Management Sciences (INFORMS)
    Publication Date: 1998
    detail.hit.zdb_id: 2019440-7
    detail.hit.zdb_id: 123389-0
    SSG: 3,2
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  • 6
    Online Resource
    Online Resource
    Voxel-Based Solution Approaches to the Three-Dimensional Irregular Packing Problem
    Institute for Operations Research and the Management Sciences (INFORMS) ; 2023
    In:  Operations Research Vol. 71, No. 4 ( 2023-07), p. 1298-1317
    Details
    In: Operations Research, Institute for Operations Research and the Management Sciences (INFORMS), Vol. 71, No. 4 ( 2023-07), p. 1298-1317
    Abstract: Research on the three-dimensional (3D) packing problem has largely focused on packing boxes for the transportation of goods. As a result, there has been little focus on packing irregular shapes in the operational research literature. New technologies have raised the practical importance of 3D irregular packing problems and the need for efficient solutions. In this work, we address the variant of the problem where the aim is to place a set of 3D irregular items in a container, while minimizing the container height, analogous to the strip packing problem. In order to solve this problem, we need to address two critical components; efficient computation of the geometry and finding high-quality solutions. In this work, we explore the potential of voxels, the 3D equivalent of pixels, as the geometric representation of the irregular items. In this discretised space, we develop a geometric tool that extends the concept of the nofit polygon to the 3D case. This enables us to provide an integer linear programming formulation for this problem that can solve some small instances. For practical size problems, we design metaheuristic optimisation approaches. Because the literature is limited, we introduce new benchmark instances. Some are randomly generated and some represent realistic models from the additive manufacturing area. Our results on the literature benchmark data and on our new instances show that our metaheuristic techniques achieve the best known solutions for a wide variety of problems in practical computation times. Supplemental Material: The e-companion is available at https://doi.org/10.1287/opre.2022.2260 .
    Type of Medium: Online Resource
    ISSN: 0030-364X , 1526-5463
    URL: Article
    DOI: 10.1287/opre.2022.2260
    RVK:
    SA 7410
    Language: English
    Publisher: Institute for Operations Research and the Management Sciences (INFORMS)
    Publication Date: 2023
    detail.hit.zdb_id: 2019440-7
    detail.hit.zdb_id: 123389-0
    SSG: 3,2
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