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Inmaculada Rodríguez-Martín

Bio: Inmaculada Rodríguez-Martín is an academic researcher from University of La Laguna. The author has contributed to research in topics: Heuristic & Vehicle routing problem. The author has an hindex of 11, co-authored 21 publications receiving 484 citations.

Papers
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Journal ArticleDOI
TL;DR: A mixed integer programming formulation for this hub location and routing problem is proposed and a branch-and-cut algorithm is developed which is tested on CAB and AP instances from the literature and shown to be strong and able to solve instances with up to 50 nodes.

83 citations

Journal ArticleDOI
TL;DR: This paper proposes a hybrid algorithm that combines the GRASP and VND metaheuristics and shows that the hybrid method yields better results than the previously proposed approaches.

77 citations

Journal ArticleDOI
TL;DR: This paper presents a mixed integer linear programming formulation and describes two branch-and-cut algorithms based on decomposition techniques and proposes a heuristic approach based on a linear programming relaxation of the mixed integer model.

68 citations

Journal ArticleDOI
TL;DR: A new heuristic approach for the capacitated fixed-charge network design problem, using local branching to use a general MIP solver to explore neighborhoods, which outperforms the best heuristic approaches found in the literature.

65 citations

Journal ArticleDOI
TL;DR: In this article, the PCLP is formulated as an integer linear program, a branch-and-cut algorithm is developed, and computational results on real-world data and randomly generated instances are presented.
Abstract: The Plant-Cycle Location Problem (PCLP) is defined on a graph G=(I∪J, E), where I is the set of customers and J is the set of plants. Each customer must be served by one plant, and the plant must be opened to serve customers. The number of customers that a plant can serve is limited. There is a cost of opening a plant, and of serving a customer from an open plant. All customers served by a plant are in a cycle containing the plant, and there is a routing cost associated to each edge of the cycle. The PCLP consists in determining which plants to open, the assignment of customers to plants, and the cycles containing each open plant and its customers, minimizing the total cost. It is an NP-hard optimization problem arising in routing and telecommunications. In this article, the PCLP is formulated as an integer linear program, a branch-and-cut algorithm is developed, and computational results on real-world data and randomly generated instances are presented. The proposed approach is able to find optimal solutions of random instances with up to 100 customers and 100 potential plants, and of instances on real-world data with up to 120 customers and 16 potential plants.

43 citations


Cited by
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15 Mar 1979
TL;DR: In this article, the experimental estimation of parameters for models can be solved through use of the likelihood ratio test, with particular attention to photon counting experiments, and procedures presented solve a greater range of problems than those currently in use, yet are no more difficult to apply.
Abstract: Many problems in the experimental estimation of parameters for models can be solved through use of the likelihood ratio test. Applications of the likelihood ratio, with particular attention to photon counting experiments, are discussed. The procedures presented solve a greater range of problems than those currently in use, yet are no more difficult to apply. The procedures are proved analytically, and examples from current problems in astronomy are discussed.

1,748 citations

Journal ArticleDOI
TL;DR: This paper proposes a classification scheme and looks at a number of problem variants in location-routing: a relatively new branch of locational analysis that takes into account vehicle routing aspects.

907 citations

Journal Article
TL;DR: In this paper, integer programming formulations for four types of discrete hub location problems are presented: the p-hub median problem, the uncapacitated hub location problem, p -hub center problems and hub covering problems.

727 citations

Journal ArticleDOI
TL;DR: A classification of TSPs with profits is proposed, and the existing literature is surveyed, and different classes of applications, modeling approaches, and exact or heuristic solution techniques are identified and compared.
Abstract: Traveling salesman problems with profits (TSPs with profits) are a generalization of the traveling salesman problem (TSP), where it is not necessary to visit all vertices. A profit is associated with each vertex. The overall goal is the simultaneous optimization of the collected profit and the travel costs. These two optimization criteria appear either in the objective function or as a constraint. In this paper, a classification of TSPs with profits is proposed, and the existing literature is surveyed. Different classes of applications, modeling approaches, and exact or heuristic solution techniques are identified and compared. Conclusions emphasize the interest of this class of problems, with respect to applications as well as theoretical results.

604 citations

Book ChapterDOI
01 Jan 2010
TL;DR: The purpose here is to give an accessible description of the underlying principles of iterated local search and a discussion of the main aspects that need to be taken into account for a successful application of it.
Abstract: The key idea underlying iterated local search is to focus the search not on the full space of all candidate solutions but on the solutions that are returned by some underlying algorithm, typically a local search heuristic. The resulting search behavior can be characterized as iteratively building a chain of solutions of this embedded algorithm. The result is also a conceptually simple metaheuristic that nevertheless has led to state-of-the-art algorithms for many computationally hard problems. In fact, very good performance is often already obtained by rather straightforward implementations of the metaheuristic. In addition, the modular architecture of iterated local search makes it very suitable for an algorithm engineering approach where, progressively, the algorithms’ performance can be further optimized. Our purpose here is to give an accessible description of the underlying principles of iterated local search and a discussion of the main aspects that need to be taken into account for a successful application of it. In addition, we review the most important applications of this method and discuss its relationship to other metaheuristics.

589 citations