Constructive multistart search algorithms are commonly used to address combinatorialoptimization problems;however, constructive multistart search algorithm performance is fundamentally affected by two factors: (i) Th...
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Constructive multistart search algorithms are commonly used to address combinatorialoptimization problems;however, constructive multistart search algorithm performance is fundamentally affected by two factors: (i) The choice of construction algorithm utilized and (ii) the rate of state space search redundancy. Construction algorithms are typically specific to a particular combinatorialoptimization problem;therefore, we first investigate construction algorithms for iterative hill climbing applied to the traveling salesman problem and experimentally determine the best performing algorithms. We then investigate the more general problem of utilizing record-keeping mechanisms to mitigate state space search redundancy. Our research shows that a good choice of construction algorithm paired with effective record keeping significantly improves the quality of traveling salesmen problem solutions in a constant number of state explorations. Particularly, we show that Bloom filters considerably improve time performance and solution quality for iterative hill climbing approaches to the traveling salesman problem. (C) 2014 Wiley Periodicals, Inc.
In this paper we give a recognition algorithm in O(n(n + m)) time for bipartite chain graphs, and directly calculate the density of such graphs. For their stability number and domination number, we give algorithms com...
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In this paper we give a recognition algorithm in O(n(n + m)) time for bipartite chain graphs, and directly calculate the density of such graphs. For their stability number and domination number, we give algorithms comparable to the existing ones. We point out some applications of bipartite chain graphs in chemistry and approach the Minimum Chain Completion problem.
Experimental characterization of high dimensional dynamic systems sometimes uses the proper orthogonal decomposition (POD). If there are many measurement locations and relatively fewer sensors, then steady-state behav...
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Experimental characterization of high dimensional dynamic systems sometimes uses the proper orthogonal decomposition (POD). If there are many measurement locations and relatively fewer sensors, then steady-state behavior can still be studied by sequentially taking several sets of simultaneous measurements. The number required of such sets of measurements can be minimized if we solve a combinatorialoptimization problem. We aim to bring this problem to the attention of engineering audiences, summarize some known mathematical results about this problem, and present a heuristic (suboptimal) calculation that gives reasonable, if not stellar results.
We investigate the approximability properties of several weighted problems, by comparing them with the respective unweighted problems. For an appropriate (and very general) definition of niceness. we show that if a ni...
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We investigate the approximability properties of several weighted problems, by comparing them with the respective unweighted problems. For an appropriate (and very general) definition of niceness. we show that if a nice weighted problem is hard to approximate within r. then its polynomially bounded weighted version is hard to approximate within r - o(1). Then we turn our attention to specific problems. and we show that the unweighted versions of MIN VERTEX COVER, MIN SAT. MAX CUT. MAX DICUT, MAX 2SAT, and MAX EXACT kSAT are exactly as hard to approximate as their weighted versions. We note in passing that MIN VERTEX COVER is exactly as hard to approximate as MIN SAT. In order to prove the reductions for MAX 2SAT, MAX CUT, MAX DICUT, and MAX E3SAT We introduce the new notion of "mixing" set and we give an explicit construction of such sets. These reductions give new non-approximability results for these problems. (C) 2001 Academic Press.
The problem of connection of users with access points of a wireless telecommunications network is analyzed. An approach is based on the multicriteria assignment problem. A set of criteria involves the maximum bandwidt...
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The problem of connection of users with access points of a wireless telecommunications network is analyzed. An approach is based on the multicriteria assignment problem. A set of criteria involves the maximum bandwidth, the number of simultaneously served users, service reliability requirements, etc. Restrictions on the number of users served by access points and the frequency spectrum width of an access point are discussed. The combinatorialoptimization problem employed belongs to the NP - hard class, and its solution is sought via the proposed heuristic methods. The proposed approach is illustrated by a numerical example. DOI: 10.1134/S1064226910120272
We show that several online combinatorialoptimization problems that admit efficient no-regret algorithms become computationally hard in the sleeping setting where a subset of actions becomes unavailable in each round...
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ISBN:
(纸本)9781510838819
We show that several online combinatorialoptimization problems that admit efficient no-regret algorithms become computationally hard in the sleeping setting where a subset of actions becomes unavailable in each round. Specifically, we show that the sleeping versions of these problems are at least as hard as PAC learning DNF expressions, a long standing open problem. We show hardness for the sleeping versions of Online Shortest Paths, Online Minimum Spanning Tree, Online k-Subsets, Online k-Truncated Permutations, Online Minimum Cut, and Online Bipartite Matching. The hardness result for the sleeping version of the Online Shortest Paths problem resolves an open problem presented at COLT 2015 [Koolen et al., 2015].
A new procedure of non-linear system identification is presented. The procedure employs the slowly-varying, time-dependent amplitude and phase functions of the impulse response of the system. These instantaneous chara...
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A new procedure of non-linear system identification is presented. The procedure employs the slowly-varying, time-dependent amplitude and phase functions of the impulse response of the system. These instantaneous characteristics are obtained from the ridges and skeletons of the wavelet transform. The ridge extraction procedure uses the modulus of the transform and involves a combinatorialoptimization algorithm based on simulated annealing. The method is illustrated using two simple simulated examples. It is shown that the procedure can be used for multi-degree-of-freedom systems due to the frequency localization property of the continuous Grossman-Morlet wavelets. (C) 1998 Academic Press.
In this article, we propose a meta-heuristic algorithm for solving multi-objective combinatorialoptimization problems. The proposed multi-objective combinatorialoptimization algorithm is developed by combining the g...
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In this article, we propose a meta-heuristic algorithm for solving multi-objective combinatorialoptimization problems. The proposed multi-objective combinatorialoptimization algorithm is developed by combining the good features of popular guided local search algorithms like simulated annealing (SA) and tabu search (TS). It has been organized as a multiple start algorithm to maintain a good balance between intensification and diversification. The proposed meta-heuristic algorithm is evaluated by solving the stacking sequence optimization of hybrid fiber-reinforced composite plate, cylindrical shell, and pressure vessel problems. The standard performance metrics for evaluating multi-objective optimizationalgorithms are used to demonstrate the effectiveness of the proposed algorithm over other popular evolutionary algorithms like Nondominated Sorting Genetic algorithms (NSGA-II), Pareto Archived Evolutionary Strategy (PAES), micro-GA, and Multi-Objective Particle Swarm optimization (MOPSO).
combinatorialoptimization problems under permutation property (COPP) are generally NP-hard. To address such problems, metaheuristic approaches have increasingly captured the research interest due to their abilities t...
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ISBN:
(纸本)9781467358125
combinatorialoptimization problems under permutation property (COPP) are generally NP-hard. To address such problems, metaheuristic approaches have increasingly captured the research interest due to their abilities to provide acceptable solutions in a reasonable time. This paper deals with a web based-solver destined for young researchers to solve COPP by metaheuristic approaches. This new tool will provide the opportunities to browse related works proposed for the COPP and metaheuristics. It will evaluate several versions of metaheuristic, and then, to give a best approximated solution to a studied COPP thanks to the design of experiment (DOE) module. As a first application, we will present a genetic solver tool for permutation flow shop scheduling problem.
The scheduling problem of social workers is a class of combinatorialoptimization problems that can be solved in exponential time at best. Because is belongs to class of problems known as NP-Hard, which have huge impa...
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ISBN:
(纸本)9783030617059;9783030617042
The scheduling problem of social workers is a class of combinatorialoptimization problems that can be solved in exponential time at best. Because is belongs to class of problems known as NP-Hard, which have huge impact huge impact on our society. Nowadays, the focus on the quantum computer should no longer be just for its enormous computing capacity but also for the use of its imperfection, (Noisy Intermediate-Scale Quantum (NISQ) era) to create a powerful machine learning device that uses the variational principle to solve the optimization problem by reducing their complexity's class. We propose a formulation of the Vehicle Rooting Problem (VRP) with time windows to solve efficiently the social workers schedule problem using Variational Quantum Eigensolver (VQE). The quantum feasibility of the algorithm will be modelled with docplex and tested on IBMQ computers.
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