Nenad Mladenović
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Cahiers du GERAD
In the field of Automatic Programming (AP), the solution of a problem is a program, which is usually presented by a tree with a specific structure. This tree...
BibTeX referenceContinuous variable neighborhood search (C-VNS) for solving systems of nonlinear equations
In this paper we propose C-VNS (Continuous variable neighborhood search) method for finding all solutions to a nonlinear system of equations (NSE). We tran...
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Clustering is an automated and powerful technique for data analysis. It aims to divide a given set of data points into clusters which are homogeneous and/o...
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We consider the NP-hard problem of synthesis of optimal spanning communication subgraph in a given arbitrary simple edge-weighted graph. This problem occurs ...
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We investigate the well-known NP-hard problem of finding an optimal communication subgraph in a given edge-weighted graph. This problem appears in different ...
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We consider the problem of optimal communication tree construction in a given undirected weighted graph. Such a problem occurs while minimizing the power c...
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In this paper we present our solution for the Challenge problem publicly announced by Railway Application Section (RAS), which operates within INFORMS. Varia...
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Graph theoretical heuristics are used extensively in many fields to solve approximately large scale optimization problems. Graph theoretical heuristics can a...
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Clustering addresses the problem of finding homogeneous and well-separated subsets, called clusters, from a set of given data points. In addition to the poi...
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The \(k\)
-means is a benchmark algorithm used in cluster analysis. It belongs to the large category of
heuristics based on location-allocation steps that ...
The balanced clustering problem consists of partitioning a set of \(n\)
objects into \(K\)
equal-sized clusters as long as
\(n\)
is a multiple of `(K...
In this paper we propose a new variant of the Variable Neighborhood Decomposition Search (VNDS) heuristic for solving global optimization problems and apply ...
BibTeX referenceVariable neighborhood programming - A new automatic programming method in artificial intelligence
Automatic programming is an efficient technique that has contributed to an important development in the artificial intelligence field. In this paper, we intr...
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Variable neighborhood search (VNS) is a framework for building heuristics, based upon systematic changes of neighborhoods both in a descent phase, to find a...
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In this paper, the first steps toward the use of the Variable Neighborhood Search metaheuristic are explained. The method is presented step by step using an...
BibTeX referenceSolving the maximally diverse grouping problem by skewed general variable neighborhood search
The maximally diverse grouping problem requires finding a partition of a given set of elements into a fixed number of mutually disjoint subsets (or groups) i...
BibTeX referenceAdaptive general variable neighborhood search heuristics for solving unit commitment problem
Unit commitment problem (UCP) for thermal units consists of finding an optimal electricity production plan for a long time horizon. In this paper we propose ...
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In this paper we propose a general variable neighborhood search heuristic for solving the uncapacitated single allocation p-hub center problem (USApHCP). F...
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The p-hub median problem consists of choosing p hub locations from a set of nodes with pairwise traffic demands in order to route the traffic between th...
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In this paper we study the periodic maintenance problem: given a set of m machines and a horizon of T periods, find indefinitely repeating itself mainten...
BibTeX referenceLess is more: Basic variable neighborhood search for Minimum differential dispersion problem
Large size optimization problems are usually successfully solved by using some metaheuristic approach. Nowadays, there is a trend to combine several metaheur...
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The uncapacitated multiple allocation p-hub center problem (UMApHCP) consists of choosing p hub locations from a set of nodes with pairwise traffic deman...
BibTeX referenceSequential variable neighborhood descent variants: An empirical study on Travelling salesman problem
Usually several neighborhood structures may be explored within a single local search algorithm. The simplest way is to define a single neighborhood as a unio...
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In this paper, we propose two new diving heuristics for finding a feasible solution for a mixed integer programming problem, called _variable neighbourhood (...
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In this paper we show that the Clique Partitioning Problem can be reformulated in an equivalent form as the Maximally Diverse Grouping Problem (MDGP). We th...
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The analysis of networks and in particular the identification of communities, or clusters, is a topic of active research with application arising in many dom...
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In this paper we evaluate the performance and compare 19 different heuristics for solving continuous global optimization. They are all based on the following...
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In this paper, we suggest DE-VNS as a new heuristic that combines two well known metaheuristic approaches: Differential Evolution (DE) and Variable Neighbour...
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Variable neighborhood search (VNS) is a meta-heuristic for solving optimization problems, whose basic idea is a systematic change of neighborhood structure...
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Attractive travelling salesman problem (AtTSP) consists of finding maximal profit tour starting and ending at a given depot after visiting some of the faci...
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This paper addresses the NP hard optimization problem of packing identical spheres of unit radii into the smallest sphere (PSS). It models PSS as a non-li...
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A travelling deliveryman needs to find a tour such that the total waiting time of all the customers he has to visit is minimum. The deliveryman starts his ...
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Euclidean Minimum Sum-of-Squares Clustering amounts to finding <i>p</i> prototypes by minimizing the sum of the squared Euclidean distances from a set of ...
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Although General Variable Neighborhood Search (GVNS) is shown to be powerful and robust methodology for solving travelling salesman and vehicle routing pro...
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Sequential clustering aims at determining homogeneous and/or well-separated clusters within a given set of entities, one at a time, until no more such clus...
BibTeX referenceSum-of-Squares Clustering on Networks
Finding <i>p</i> prototypes by minimizing the sum of the squared distances from a set of points to its closest prototype is a well-studied problem in cluste...
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A travelling deliveryman needs to find a tour, such that the total waiting time of all his customers is minimum. The Deliveryman starts his tour at a depot...
BibTeX referenceDegeneracy of Harmonic Means Clustering
It is well known that some local search algorithms for <i>K</i>-clustering problems could stop at a solution with fewer clusters than the desired <i>K</i>....
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We present a Variable Neighborhood Search approach to solving the one-commodity pickup-and-delivery travelling salesman problem. It is characterized by a s...
BibTeX referenceMaximizing Edge-Ratio Is NP-Complete
Given a graph <i>G</i> and a bipartition of its vertices, the edge-ratio is the minimum for both classes so defined of their number of internal edges divid...
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Censored quantile regression models are very useful for the analysis of censored data when standard linear models are felt to be appropriate. However, fitt...
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In this paper an effective modification to the original Nelder-Mead simplex method is suggested. It is shown that the new heuristic outperforms on average ...
BibTeX referenceVariable Neighborhood Search for Metric Dimension and Minimal Doubly Resolving Set Problems
In this paper we consider two similar NP-hard optimization problems on graphs: the metric dimension problem and the problem of determining minimal doubly r...
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Variable Neighborhood Search (VNS) has shown to be a powerful tool for solving both discrete and box-constrained continuous optimization problems. In this ...
BibTeX referenceVariable Neighbourhood Decomposition Search with Pseudo-Cuts for Multidimensional Knapsack Problem
In this paper we propose new matheuristics for solving multidimensional knapsack problem. They are based on the variable neighbourhood decomposition search (...
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We present a new general variable neighborhood search approach for the uncapacitated single allocation <i>p</i>-hub median problem in networks. This NP-hard ...
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In this paper we propose a new hybrid heuristic for solving 0-1 mixed integer programs based on the principle of variable neighbourhood decomposition search....
BibTeX referenceA Variable Neighborhood Search Based Algorithm for Finite-Horizon Markov Decision Processes
This paper considers the application of a Variable Neighborhood Search (VNS) algorithm for finite-horizon (<i>H</i> stages) Markov Decision Processes (MDPs),...
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Harmonic means clustering is a variant of Minimum sum of squares clustering (which is sometimes called <i>K</i>-means clustering), designed to alleviate the ...
BibTeX referenceVariable Neighborhood Search
Variable neighborhood search (VNS) is a metaheuristic for solving combinatorial and global optimization problems whose basic idea is a systematic change o...
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Variable neighborhood search (VNS) is a metaheuristic, or framework for building heuristics, based upon systematic change of neighborhoods both in a decent ...
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The problem of reducing the bandwidth of a matrix consists of finding a permutation of rows and columns of a given matrix that keeps the non-zero elements in...
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In this note we suggest a simple but efficient modification of the well-known Nelder-Mead (NM) simplex search method for unconstrained optimization. Instead ...
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We consider one of the most important issues for multinationals, the determination of transfer prices. To do so, we examine the example of a multinational co...
BibTeX referenceVariable Neighborhood Search Methods
Main methods, algorithms and applications of the Variable Neighborhood Search metaheuristic are surveyed, in view of a chapter of the <i>Encyclopedia of Opti...
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Circle packing problems were recently solved via reformulation descent (RD) by switching between a cartesian and a polar formulation. Mixed formulations, wi...
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Data clustering methods have been developed extensively in the data mining literature for detecting useful patterns in large datasets in the form of dense...
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In this survey, we examine an important class of facility location problems known as the multisource Weber problem (also referred to as the continuous locat...
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A recent comparison of evolutionary, neural network, and scatter search heuristics for solving the p-median problem is completed by (i) gathering or obtaini...
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This paper presents a new method for the probabilistic logic satisfiability problem, based on the variable neighborhood search metaheuristic. The solution s...
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We suggest new heuristic for solving unconstrained continuous optimization problems. It is based on generalized version of the variable neighborhood search m...
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Colour image quantization is a data compression technique that reduces the total set of colours in an image to a representative subset. This problem is expr...
BibTeX referenceExtension of the Weiszfeld Procedure to a Single Facility Minisum Location Model with Mixed Norms
This paper presents a general mixed-norm minisum problem for locating a single facility in continuous space. It is assumed that several transportation modes...
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The <i>p</i>-median problem is one of the basic models in discrete location theory. As with most location problems, it is classified as NP-hard, and so, heu...
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The variable neighborhood search metaheuristic is applied to the primal simple plant location problem and to a reduced dual obtained by exploiting the compl...
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This paper examines the plant location problem under the objective of maximizing return-on-investment. However, in place of the standard assumption that all...
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We present a MILP mathematical programming formulation for static scheduling of dependent tasks onto homogeneous multiprocessor system of an arbitrary archi...
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The continuous location-allocation problem requires finding sites for <i>m</i> new facilities in the plane in order to serve <i>n</i> users such that the to...
BibTeX referenceParallel Variable Neighborhood Search
Variable Neighborhood Search (VNS) is a recent and effective metaheuristic for solving combinatorial and global optimization problems. It is capable of esca...
BibTeX referenceAnalysis of Global k-Means, an Incremental Heuristic for Minimum Sum-of-Squares Clustering
The global <i>k</i>-means heuristic is a recently proposed (Likas et al. 2003) incremental approach for minimum sum-of-squares clustering of a set <i>X</i> ...
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In this paper we develop a Variable neighborhood search (VNS) heuristic for solving Mixed-Integer Programs (MIP’s). It uses CPLEX, the general-purpose MIP s...
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We describe an application of Variable Neighbourhood Search (VNS)methodology to continuous global optimization problems with box constraints. A general VNS a...
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In this work we propose to use a continuous Variable Neighborhood Search (VNS for short) heuristic for minimizing the potential energy function of molecules...
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This paper presents some new heuristics based on variable neighborhood search to solve the vertex weighted <i>k</i>-cardinality tree problem. An efficient l...
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We consider the bilevel uncapacitated facility location problem with user preferences. It is known that this model may be reformulated as a one-level locati...
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The multiprocessor scheduling problem with communication delays that we consider in this paper consists of finding a static schedule of an arbitrary task gra...
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In this note we explore the fact that a stationary point of some nonlinear non-convex optimization problem is not always a local optimum, and that such a st...
BibTeX referenceDesign of Balanced MBA Student Teams
In some schools and universities, students must sometimes be divided into several teams in such a way that each team provides a good representation of the cl...
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A constant fixed cost of establishing a facility is introduced within the framework of minisum facility location in the continuous space. The solution metho...
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This paper examines the convergence properties of two well-known heuristics: variable neighborhood search (VNS) and random multistart local search (MLS). Bot...
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When applying the 2-opt heuristic to the travelling salesman problem, selecting the best improvement at each iteration gives worse results on average than se...
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The berth allocation problem is to allocate space along the quayside to incoming ship at a container terminal in order to minimize some objective function....
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Variable Neighborhood Search (VNS) is a recent metaheuristic, or framework for building heuristics, which exploits systematically the idea of neighborhood ch...
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We develop and analyze parallelization strategies for the Variable Neighborhood Search (VNS) meta-heuristic applied to the <i>p</i>-median problem. The stra...
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This paper studies the duality gap in the simple plant location problem, and presents general formulas for the gap when certain complementary slackness cond...
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The pooling problem, which is fundamental to the petroleum industry, describes a situation where products possessing different attribute qualities are mixed...
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Minimum <i>k</i>-cardinality tree problem on graph <i>G</i> consists in finding a subtree of <i>G</i> with exactly <i>k</i> edges whose sum of weights is mi...
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Variable neighborhood search (VNS) is a recent metaheuristic for solving combinatorial and global optimization problems whose basic idea is systematic chang...
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Proposed just a few years ago, Variable Neighborhood Search (VNS) is a new metaheuristic for combinatorial and global optimization, based upon systematic ch...
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Reduction of some classes of global optimization programs to bilinear programs may be done in various ways, and the choice of method clearly influences the ...
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The <i>p</i>-Center problem consists in locating <i>p</i> facilities and assigning clients to them in order to minimize the maximum distance between a clien...
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A fuzzy clustering problem consists in assigning a set of patterns to a given number of clusters with respect to some criteria such that each of them may be...
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Maximum Clique is one of the most studied NP-hard optimization problem on graphs because of its simplicity and its numerous applications. A basic Variable N...
BibTeX referenceRecherche à Voisinage Variable
La Recherche à Voisinage Variable (RVV) est une métaheuristique récente basée sur l'idée d'un chargement systématique de voisinage, à la fois dans une phase...
BibTeX referenceAn Oil Pipeline Design Problem
We consider a given set of offshore platforms and onshore wells, producing known (or estimated) amounts of oil, to be connected to a port. Connections may t...
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Variable Neighborhood Search (VNS) is a recent metaheuristic which exploits systematically the idea of change of neighborhood within the search. After recal...
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Given a set of logical sentences together with nonnegative weights assigned to each of them, the Maximum Weight Satisfiability problem (MAX-WEIGHT SAT) cons...
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A Basic Variable Neighbourhood Search heuristic is applied to min-max global optimization problems. The method is tested on the spread spectrum radar polyph...
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The continuous <i>p</i>-defense-sum problem consists of locating <i>p</i> facilities in a convex polyhedron, such that the sum of the distances among all th...
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The standard way to solve the static economic dispatch problem with transmission losses is the penalty factor method. The problem is solved iteratively by a...
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Systematic change of neighborhood within a possibly randomized local search algorithm yields a simple and effective metaheuristic for combinatorial and glo...
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Variable Neighborhood Search is a recent metaheuristic based on the idea of systematic change of neighborhood during both a descent phase and an exploration...
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A new local search heuristic, called J-MEANS, is proposed for solving the minimum sum-of-squares clustering problem. The neighborhood of the current solut...
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The recent Variable Neighborhood Search (VNS) metaheuristic combines local search with systematic changes of neighborhood in the descent and escape from loc...
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An exact algorithm is proposed for minimum sum-of-squares nonhierarchical clustering, i.e., for partitioning a given set of points from Euclidean <i>m</i>-s...
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This study investigates a new phenomenon of degeneracy in the multi-source Weber problem. This phenomenon relates to the existence of solutions in which one...
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Systematic change of neighborhood within a possibly randomized local search algorithm yields a simple and effective metaheuristic for combinatorial and glo...
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Consider a set <i>L</i> of potential locations for <i>p</i> facilities and a set <i>U</i> of locations of given users. The <i>p</i>-median problem is to loc...
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Good heuristic solutions for large Multisource Weber problems can be obtained by solving related <i>p</i>-median problems in which potential locations of th...
BibTeX referenceVariable Neighbourhood Search
Systematic change of neighborhood within a local search algorithm yields a simple and effective metaheuristic for combinatorial optimization. We present a ...
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The multisource Weber problem is to locate simultaneously <i>m</i> facilities in the Euclidean plane in order to minimize the total transportation cost for ...
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Clustering with a criterion which minimizes the sum of squared distances to cluster centroids is usually done in a heuristic way. An exact polynomial algori...
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This paper investigates a new phenomenon of degeneracy in the continuous location-allocation problem. This phenomenon relates to the existence of solutions ...
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Extension of input-output functions for generating units allows simultaneous solution of the static unit commitment and economic dispatch problems by dynami...
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Local descent methods typically employ a single neighbourhood structure to conduct the search around a candidate solution. In this paper, we propose a metho...
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A new category of Tabu search, Chain-interchange heuristic method is proposed in this paper. It can be viewed as a Tabu search method adopted for a large c...
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Several heuristic methods have been developed to solve the location-allocation problem in continuous space. Typically, these algorithms attempt to move in d...
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The multi-source Weber problem requires locating <i>m</i> new facilities in continuous space in order to minimize a sum of transportation costs to <i>n</i> ...
BibTeX referenceHow to Choose K Entities Among N
A new paradigm for cluster analysis is outlined. It is called Sequential Clustering. Given a set <i>O</i> of <i>N</i> entities a best cluster of <i>K</i> ...
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Five recent practically efficient methods for solving the maximum clique problem are briefly described and compared on randomly generated graphs. A Fortran ...
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It is shown that any vertex which is simplicial in the complementary graph of a given graph belongs to at least one maximum clique of that graph. This prope...
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