Results 1 
7 of
7
Metaheuristics in combinatorial optimization: Overview and conceptual comparison
 ACM COMPUTING SURVEYS
, 2003
"... The field of metaheuristics for the application to combinatorial optimization problems is a rapidly growing field of research. This is due to the importance of combinatorial optimization problems for the scientific as well as the industrial world. We give a survey of the nowadays most important meta ..."
Abstract

Cited by 294 (16 self)
 Add to MetaCart
The field of metaheuristics for the application to combinatorial optimization problems is a rapidly growing field of research. This is due to the importance of combinatorial optimization problems for the scientific as well as the industrial world. We give a survey of the nowadays most important metaheuristics from a conceptual point of view. We outline the different components and concepts that are used in the different metaheuristics in order to analyze their similarities and differences. Two very important concepts in metaheuristics are intensification and diversification. These are the two forces that largely determine the behaviour of a metaheuristic. They are in some way contrary but also complementary to each other. We introduce a framework, that we call the I&D frame, in order to put different intensification and diversification components into relation with each other. Outlining the advantages and disadvantages of different metaheuristic approaches we conclude by pointing out the importance of hybridization of metaheuristics as well as the integration of metaheuristics and other methods for optimization.
Analyzing the landscape of a graph based hyperheuristic for timetabling problems
 In Proceedings of Genetic and Evolutionary Computation Conference (GECCO 2009
, 2009
"... Hyperheuristics can be thought of as “heuristics to choose heuristics”. They are concerned with adaptively finding solution methods, rather than directly producing a solution for the particular problem at hand. Hence, an important feature of hyperheuristics is that they operate on a search space o ..."
Abstract

Cited by 8 (4 self)
 Add to MetaCart
(Show Context)
Hyperheuristics can be thought of as “heuristics to choose heuristics”. They are concerned with adaptively finding solution methods, rather than directly producing a solution for the particular problem at hand. Hence, an important feature of hyperheuristics is that they operate on a search space of heuristics rather than directly on a search space of problem solutions. A motivating aim is to build systems which are fundamentally more generic than is possible today. Understanding the structure of these heuristic search spaces is therefore, a research direction worth exploring. In this paper, we use the notion of fitness landscapes in the context of constructive hyperheuristics. We conduct a landscape analysis on a heuristic search space conformed by sequences of graph coloring heuristics for timetabling. Our study reveals that these landscapes have a high level of neutrality and positional bias. Furthermore, although rugged, they have the encouraging feature of a globally convex or big valley structure, which indicates that an optimal solution would not be isolated but surrounded by many local minima. We suggest that using search methodologies that explicitly exploit these features may enhance the performance of constructive hyperheuristics.
Phase transition in a random NK landscape model
, 2008
"... An analysis for the phase transition in a random NK landscape model, NK(n,k,z), is given. This model is motivated from population genetics and the solubility problem for the model is equivalent to a random (k + 1)SAT problem. Gao and Culberson [Y. Gao, J. Culberson, An analysis of phase transition ..."
Abstract

Cited by 7 (0 self)
 Add to MetaCart
(Show Context)
An analysis for the phase transition in a random NK landscape model, NK(n,k,z), is given. This model is motivated from population genetics and the solubility problem for the model is equivalent to a random (k + 1)SAT problem. Gao and Culberson [Y. Gao, J. Culberson, An analysis of phase transition in NK landscapes, Journal of Artificial Intelligence Research 17 (2002) 309–332] showed that a random instance generated by NK(n, 2,z) with z>z0 = 27−7√5 4 is asymptotically insoluble. Based on empirical results, they conjectured that the phase transition occurs around the value z = z0. We prove that an instance generated by NK(n, 2,z)with z<z0 is soluble with positive probability by providing a polynomial time algorithm. Using branching process arguments, we prove again that an instance generated by NK(n, 2,z)with z>z0 is asymptotically insoluble. The results show the phase transition around z = z0 for NK(n, 2,z). In the course of the analysis, we introduce a generalized random 2SAT formula, which is of self interest, and show its phase transition phenomenon.
Correlation analysis of coupled fitness landscapes
 Complexity
"... ∗ Author for correspondence The correlation structure of fitness landscapes is a much used measure to characterize and classify various types of landscapes. However, analyzing the correlation structure of fitness landscapes has so far been restricted to static landscapes only. Here, we investigate t ..."
Abstract

Cited by 4 (0 self)
 Add to MetaCart
∗ Author for correspondence The correlation structure of fitness landscapes is a much used measure to characterize and classify various types of landscapes. However, analyzing the correlation structure of fitness landscapes has so far been restricted to static landscapes only. Here, we investigate the correlation structure of coupled, or dynamic, fitness landscapes. Using the NKC model of coevolution, we apply a correlation analysis on various instances of this model and present the results. One of the main goals of this paper is thus to show that a previously introduced correlation analysis can be successfully extended to coupled fitness landscapes. Furthermore, our analysis shows that this provides meaningful and interesting results that can contribute to a better understanding of coevolution in general. 1
Decision making in an Adaptive Reservoir
"... It is now common knowledge that blind search algorithms cannot perform with equal e#ciency on all possible optimization problems defined on a domain. This knowledge applies also to Genetic Algorithms when viewed as global and blind optimizers. From this point of view it is necessary to design al ..."
Abstract
 Add to MetaCart
It is now common knowledge that blind search algorithms cannot perform with equal e#ciency on all possible optimization problems defined on a domain. This knowledge applies also to Genetic Algorithms when viewed as global and blind optimizers. From this point of view it is necessary to design algorithms capable of adapting their search behaviour by making use in a direct fashion of the knowledge pertaining to the search landscape. The paper introduces a novel adaptive Genetic Algorithm where the exploration/exploitation balance is directly controlled using a Bayesian decision process. Test cases are analyzed as to how parameters a#ect the search behaviour of the algorithm.
EN
"... Simulation has been used to model combat for a long time. Recently, it has been accepted that combat is a complex adaptive system (CAS). Multiagent systems (MAS) are also considered as a powerful modelling and development environment to simulate combat. Agentbased distillations (ABD) proposed by ..."
Abstract
 Add to MetaCart
(Show Context)
Simulation has been used to model combat for a long time. Recently, it has been accepted that combat is a complex adaptive system (CAS). Multiagent systems (MAS) are also considered as a powerful modelling and development environment to simulate combat. Agentbased distillations (ABD) proposed by the US Marine Corp are a type of MAS used mainly by the military for exploring large scenario spaces. ABDs that facilitated the analysis and understanding of combat include: ISAAC, EINSTein, MANA, CROCADILE and BactoWars. With new concepts such as networked forces, previous ABDs can implicitly simulate a networked force. However, the architectures of these systems limit the potential advantages gained from the use of networks. In this thesis, a novel network centric multiagent architecture (NCMAA) is proposed, based purely on network theory and CAS. In NCMAA, each relationship and interaction is modelled as a network, with the entities or agents as the nodes. NCMAA offers the following advantages:
Empirically Evaluated Improvements To Genotypic Spatial Distance Measurement Approaches For The Genetic Algorithm
"... The ability to visualize a solution space can be very beneficial, and it is generally accepted that the objective of visualization is to aid researchers in gathering insight. However, insight cannot be gathered effectively if the source data is misrepresented. This dissertation begins by demonstrati ..."
Abstract
 Add to MetaCart
(Show Context)
The ability to visualize a solution space can be very beneficial, and it is generally accepted that the objective of visualization is to aid researchers in gathering insight. However, insight cannot be gathered effectively if the source data is misrepresented. This dissertation begins by demonstrating that the adaptive landscape visualization in widespread usage frequently misrepresents the neighborhood structure of genotypic space and, consequently, will mislead users about the manner in which solution space is traversed by the genetic algorithm. Bernhard Riemann, the father of topology, explicitly noted that a measurement of the distance between entities should represent the manner in which one can be brought towards the other. Thus, the commonly used Hamming distance, for example, is not representative of traversals of genotypic space by the genetic algorithm – a representative measure must include consideration for both mutation and recombination. This dissertation separately explores the properties that mutational and recombinational distances should have, and ultimately establishes a measure that is representative of the traversals made by both operators simultaneously. It follows that these measures can be used to enhance the adaptive landscape, by