The Vehicle Routing Problem (VRP) was introduced 50 years ago by Dantzig and Ramser under the title "The Truck Dispatching Problem." The study of the VRP has given rise to major developments in the fields of...
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The Vehicle Routing Problem (VRP) was introduced 50 years ago by Dantzig and Ramser under the title "The Truck Dispatching Problem." The study of the VRP has given rise to major developments in the fields of exact algorithms and heuristics. In particular, highly sophisticated exact mathematical programming decomposition algorithms and powerful metaheuristics for the VRP have been put forward in recent years. The purpose of this article is to provide a brief account of this development.
We consider the Partition Into Triangles problem on bounded degree graphs. We show that this problem is polynomial-time solvable on graphs of maximum degree three by giving a linear-time algorithm. We also show that t...
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We consider the Partition Into Triangles problem on bounded degree graphs. We show that this problem is polynomial-time solvable on graphs of maximum degree three by giving a linear-time algorithm. We also show that this problem becomes -complete on graphs of maximum degree four. Moreover, we show that there is no subexponential-time algorithm for this problem on graphs of maximum degree four unless the Exponential-Time Hypothesis fails. However, the Partition Into Triangles problem on graphs of maximum degree at most four is in many cases practically solvable as we give an algorithm for this problem that runs in time and linear space.
We consider stochastic problems in which both the objective function and the feasible set are affected by uncertainty. We address these problems using a K-adaptability approach, in which K solutions for a given proble...
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We consider stochastic problems in which both the objective function and the feasible set are affected by uncertainty. We address these problems using a K-adaptability approach, in which K solutions for a given problem are computed before the uncertainty dissolves and afterwards the best of them can be chosen for the realized scenario. We analyze the complexity of the resulting problem from a theoretical viewpoint, showing that, even in case the deterministic problem can be solved in polynomial time, deciding if a feasible solution exists is NP-hard for discrete probability distributions. Besides that, we prove that an approximation factor for the underlying problem can be carried over to our problem. Finally, we present exact approaches including a branch-and-price algorithm. An extensive computational analysis compares the performances of the proposed algorithms on a large set of randomly generated instances.
We present a framework for an automated generation of exact search tree algorithms for NP-hard problems. The purpose of our approach is twofold-rapid development and improved upper bounds. Many search tree algorithms ...
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We present a framework for an automated generation of exact search tree algorithms for NP-hard problems. The purpose of our approach is twofold-rapid development and improved upper bounds. Many search tree algorithms for various problems in the literature are based on complicated case distinctions. Our approach may lead to a much simpler process of developing and analyzing these algorithms. Moreover, using the sheer computing power of machines it may also lead to improved upper bounds on search tree sizes (i.e., faster exact solving algorithms) in comparison with previously developed "hand-made" search trees. Among others, such an example is given with the NP-complete Cluster Editing problem (also known as Correlation Clustering on complete unweighted graphs), which asks for the minimum number of edge additions and deletions to create a graph which is a disjoint union of cliques. The hand-made search tree for Cluster Editing had worst-case size O(2.27(k)), which now is improved to O(1.92(k)) due to our new method. (Herein, k denotes the number of edge modifications allowed.).
We consider the problem of orthogonally packing a given set of rectangular-shaped boxes into the minimum number of three-dimensional rectangular bins. The problem is NP-hard in the strong sense and extremely difficult...
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We consider the problem of orthogonally packing a given set of rectangular-shaped boxes into the minimum number of three-dimensional rectangular bins. The problem is NP-hard in the strong sense and extremely difficult to solve in practice. We characterize relevant subclasses of packing and present an algorithm which is able to solve moderately large instances to optimality. Extensive computational experiments compare the algorithm for the three-dimensional bin packing when solving general orthogonal packings and when restricted to robot packings.
The 2-Disjoint Connected Subgraphs problem, given a graph along with two disjoint sets of terminals Z (1),Z (2), asks whether it is possible to find disjoint sets A (1),A (2), such that Z (1)aS dagger A (1), Z (2)aS d...
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The 2-Disjoint Connected Subgraphs problem, given a graph along with two disjoint sets of terminals Z (1),Z (2), asks whether it is possible to find disjoint sets A (1),A (2), such that Z (1)aS dagger A (1), Z (2)aS dagger A (2) and A (1),A (2) induce connected subgraphs. While the naive algorithm runs in O(2 (n) n (O(1))) time, solutions with complexity of form O((2-epsilon) (n) ) have been found only for special graph classes (van 't Hof et al. in Theor. Comput. Sci. 410(47-49):4834-4843, 2009;Paulusma and van Rooij in Theor. Comput. Sci. 412(48):6761-6769, 2011). In this paper we present an O(1.933 (n) ) algorithm for 2-Disjoint Connected Subgraphs in general case, thus breaking the 2 (n) barrier. As a counterpoise of this result we show that if we parameterize the problem by the number of non-terminal vertices, it is hard both to speed up the brute-force approach and to find a polynomial kernel.
The goal Of the CLUSTER EDITING problem is to make the fewest changes to the edge set of an input graph such that the resulting graph is a disjoint union Of cliques. This problem is NP-complete but recently, several p...
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The goal Of the CLUSTER EDITING problem is to make the fewest changes to the edge set of an input graph such that the resulting graph is a disjoint union Of cliques. This problem is NP-complete but recently, several parameterized algorithms have been proposed. In this paper, we present a number of surprisingly simple search tree algorithms for WEIGHTED CLUSTER EDITING assuming that edge insertion and deletion costs are positive integers. We show that the smallest search tree has size O(1.82(k)) for edit cost k, resulting in the currently fastest parameterized algorithm, both for this problem and its unweighted counterpart. We have implemented and compared our algorithms, and achieved promising results.(1) (C) 2009 Elsevier B.V. All rights reserved.
The maximum clique problem (MCP) is to determine in a graph a clique (i.e., a complete subgraph) of maximum cardinality. The MCP is notable for its capability of modeling other combinatorial problems and real-world ap...
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The maximum clique problem (MCP) is to determine in a graph a clique (i.e., a complete subgraph) of maximum cardinality. The MCP is notable for its capability of modeling other combinatorial problems and real-world applications. As one of the most studied NP-hard problems, many algorithms are available in the literature and new methods are continually being proposed. Given that the two existing surveys on the MCP date back to 1994 and 1999 respectively, one primary goal of this paper is to provide an updated and comprehensive review on both exact and heuristic MCP algorithms, with a special focus on recent developments. To be informative, we identify the general framework followed by these algorithms and pinpoint the key ingredients that make them successful. By classifying the main search strategies and putting forward the critical elements of the most relevant clique methods, this review intends to encourage future development of more powerful methods and motivate new applications of the clique approaches. (C) 2014 Elsevier B.V. All rights reserved.
A formulation is proposed for the perfect edge domination problem and some exact algorithms based on it are designed and tested. So far, perfect edge domination has been investigated mostly in computational complexity...
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A formulation is proposed for the perfect edge domination problem and some exact algorithms based on it are designed and tested. So far, perfect edge domination has been investigated mostly in computational complexity terms. Indeed, we could find no previous explicit mathematical formulation or exact algorithm for the problem. Furthermore, testing our algorithms also represented a challenge. Standard randomly generated graphs tend to contain a single perfect edge dominating solution, i.e., the trivial one, containing all edges in the graph. Accordingly, some quite elaborated procedures had to be devised to have access to more challenging instances. A total of 736 graphs were thus generated, all of them containing feasible solutions other than the trivial ones. Every graph giving rise to a weighted and a non weighted instance, all instances solved to proven optimality by two of the algorithms tested.
In this paper, we consider the (n,3)-MAXSAT problem. The problem is a special case of the Maximum Satisfiability problem with an additional requirement that in the input formula each variable appears at most three tim...
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In this paper, we consider the (n,3)-MAXSAT problem. The problem is a special case of the Maximum Satisfiability problem with an additional requirement that in the input formula each variable appears at most three times. Here, we improve previous upper bounds for (n,3)-MAXSAT in terms of n (number of variables) and in terms of k (number of clauses that we are required to satisfy). Moreover, we prove that satisfying more clauses than the simple all true assignment is an NP-hard problem. (C) 2019 Elsevier B.V. All rights reserved.
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