Results 1  10
of
14
Topological Interpretation of Crossover
 IN PROCEEDINGS OF THE GENETIC AND EVOLUTIONARY COMPUTATION CONFERENCE
, 2004
"... In this paper we give a representationindependent topological definition of crossover that links it tightly to the notion of fitness landscape. Building around this definition, a geometric/topological framework for evolutionary algorithms is introduced that clarifies the connection between repre ..."
Abstract

Cited by 39 (26 self)
 Add to MetaCart
In this paper we give a representationindependent topological definition of crossover that links it tightly to the notion of fitness landscape. Building around this definition, a geometric/topological framework for evolutionary algorithms is introduced that clarifies the connection between representation, genetic operators, neighbourhood structure and distance in the landscape. Traditional genetic operators for binary strings are shown to fit the framework. The advantages of this interpretation are discussed
Parallel estimation of distribution algorithms
, 2002
"... The thesis deals with the new evolutionary paradigm based on the concept of Estimation of Distribution Algorithms (EDAs) that use probabilistic model of promising solutions found so far to obtain new candidate solutions of optimized problem. There are six primary goals of this thesis: 1. Suggestion ..."
Abstract

Cited by 26 (4 self)
 Add to MetaCart
The thesis deals with the new evolutionary paradigm based on the concept of Estimation of Distribution Algorithms (EDAs) that use probabilistic model of promising solutions found so far to obtain new candidate solutions of optimized problem. There are six primary goals of this thesis: 1. Suggestion of a new formal description of EDA algorithm. This high level concept can be used to compare the generality of various probabilistic models by comparing the properties of underlying mappings. Also, some convergence issues are discussed and theoretical ways for further improvements are proposed. 2. Development of new probabilistic model and methods capable of dealing with continuous parameters. The resulting Mixed Bayesian Optimization Algorithm (MBOA) uses a set of decision trees to express the probability model. Its main advantage against the mostly used IDEA and EGNA approach is its backward compatibility with discrete domains, so it is uniquely capable of learning linkage between mixed continuousdiscrete genes. MBOA handles the discretization of continuous parameters as an integral part of the learning process, which outperforms the histogrambased
Geometric Crossover for the Permutation Representation
, 2005
"... Abstract. Abstract crossover and abstract mutation are representationindependent operators that are welldefined once a notion of distance over the solution space is defined. They were obtained as generalization of genetic operators for binary strings and real vectors. In this paper we explore how ..."
Abstract

Cited by 9 (6 self)
 Add to MetaCart
Abstract. Abstract crossover and abstract mutation are representationindependent operators that are welldefined once a notion of distance over the solution space is defined. They were obtained as generalization of genetic operators for binary strings and real vectors. In this paper we explore how the abstract geometric framework applies to the permutation representation. This representation is challenging for various reasons: because of the inherent difference between permutations and the representations that inspired the abstraction; because the whole notion of geometry over permutation spaces radically departs from traditional geometries and it is almost unexplored mathematical territory; because the many notions of distance available and their subtle interconnections make it hard to see the right distance to use, if any; because the various available interpretations of permutations make ambiguous what a permutation represents, hence, how to treat it; because of the existence of various permutationlike representations that are incorrectly confused with permutations; and finally because of the existence of many mutation and recombination operators and their many variations for the same representation. This article shows that the application of our geometric framework naturally clarifies and unifies an important domain, the permutation representation and the related operators, in which there was little or no hope to find order. In addition the abstract geometric framework is used to improve the design of crossover operators for wellknown problems naturally connected with the permutation representation. 1.
GUIDE: Unifying evolutionary engines through a graphical user interface
 Evolution Artificielle, 6th International Conference, volume 2936 of Lecture Notes in Computer Science
, 2003
"... er sio n 1 ..."
(Show Context)
Enhanced forma analysis of permutation problems
 In Proceedings of Genetic and Evolutionary Computation Conference 2007 (GECCO 2007
, 2007
"... Forma analysis provides an approach to formally derive domain specific operators based on domainindependent operator templates by manipulating a set of equivalence relations (i.e., the basis), which is used to describe the search space. In the case of permutation problems, where the basis is highly ..."
Abstract

Cited by 1 (0 self)
 Add to MetaCart
(Show Context)
Forma analysis provides an approach to formally derive domain specific operators based on domainindependent operator templates by manipulating a set of equivalence relations (i.e., the basis), which is used to describe the search space. In the case of permutation problems, where the basis is highly constrained, the declarative nature of forma analysis encounters some difficulties which give rise to some additional issues, such as the interpretation of declarative constraints and the complexity of the application of operator. This paper aims to address these issues by introducing Enhanced Forma Analysis that explores a broader view of forma analysis by using ideas from constraint satisfaction.
ABSTRACT
, 2006
"... The local reconstruction of a railway schedule following a small perturbation of the traffic, seeking minimization of the total accumulated delay, is a very difficult and tightly constrained combinatorial problem. Notoriously enough, the railway company’s public image degrades proportionally to the ..."
Abstract
 Add to MetaCart
(Show Context)
The local reconstruction of a railway schedule following a small perturbation of the traffic, seeking minimization of the total accumulated delay, is a very difficult and tightly constrained combinatorial problem. Notoriously enough, the railway company’s public image degrades proportionally to the amount of daily delays, and the same goes for its profit! This paper describes an inoculation procedure which greatly enhances an evolutionary algorithm for train rescheduling. The procedure consists in building the initial population around a precomputed solution based on problemrelated information available beforehand. The optimization is performed by adapting times of departure and arrival, as well as allocation of tracks, for each train at each station. This is achieved by a permutationbased evolutionary algorithm that relies on a semigreedy heuristic scheduler to gradually reconstruct the schedule by inserting trains one after another. Experimental results are presented on various instances of a large realworld case involving around 500 trains and more than 1 million constraints. In terms of competition with commercial mathematical programming tool ILOG CPLEX, it appears that within a large class of instances, excluding trivial instances as well as too difficult ones, and with very few exceptions, a clever initialization turns an encouraging failure into a clearcut success auguring of substantial financial savings.
ABSTRACT On the Spectacular Benefits of Inoculation: an Example in Train Scheduling Draft Version
"... The local reconstruction of a railway schedule following a small perturbation of the traffic, seeking minimization of the total accumulated delay, is a very difficult and tightly constrained combinatorial problem. Notoriously enough, the railway company public image degrades proportionally to the am ..."
Abstract
 Add to MetaCart
(Show Context)
The local reconstruction of a railway schedule following a small perturbation of the traffic, seeking minimization of the total accumulated delay, is a very difficult and tightly constrained combinatorial problem. Notoriously enough, the railway company public image degrades proportionally to the amount of daily delays, and the same goes for its profit! This paper describes an inoculation procedure which greatly enhances an evolutionary algorithm for train rescheduling. The procedure consists in building the initial population around a precomputed solution based on problemrelated information available beforehand. The optimization is performed by adapting times of departure and arrival, as well as allocation of tracks, for each train at each station. This is achieved by a permutationbased evolutionary algorithm that relies on a semigreedy heuristic scheduler to gradually reconstruct the schedule by inserting trains one after another. Experimental results are presented on various instances of a large realworld case involving around 500 trains and more than 1 million constraints. In terms of competition with commercial mathematical programming tool ILOG CPLEX, it appears that within a large class of instances, excluding trivial instances as well as too difficult ones, and with very few exceptions, a clever initialization turns an encouraging failure into a clearcut success auguring of substantial financial savings. Categories and Subject Descriptors H.4 [Information Systems Applications]: Miscellaneous; D.2.8 [Software Engineering]: Metrics—complexity measures,
ABSTRACT On the Benefits of Inoculation, an Example in Train Scheduling
"... The local reconstruction of a railway schedule following a small perturbation of the traffic, seeking minimization of the total accumulated delay, is a very difficult and tightly constrained combinatorial problem. Notoriously enough, the railway company’s public image degrades proportionally to the ..."
Abstract
 Add to MetaCart
(Show Context)
The local reconstruction of a railway schedule following a small perturbation of the traffic, seeking minimization of the total accumulated delay, is a very difficult and tightly constrained combinatorial problem. Notoriously enough, the railway company’s public image degrades proportionally to the amount of daily delays, and the same goes for its profit! This paper describes an inoculation procedure which greatly enhances an evolutionary algorithm for train rescheduling. The procedure consists in building the initial population around a precomputed solution based on problemrelated information available beforehand. The optimization is performed by adapting times of departure and arrival, as well as allocation of tracks, for each train at each station. This is achieved by a permutationbased evolutionary algorithm that relies on a semigreedy heuristic scheduler to gradually reconstruct the schedule by inserting trains one after another. Experimental results are presented on various instances of a large realworld case involving around 500 trains and more than 1 million constraints. In terms of competition with commercial mathematical programming tool ILOG CPLEX, it appears that within a large class of instances, excluding trivial instances as well as too difficult ones, and with very few exceptions, a clever initialization turns an encouraging failure into a clearcut success auguring of substantial financial savings.
Modelling the Performance of Evolutionary Algorithms on the Satisfiability Problem
"... Given a boolean propositional formula the satisfiability problem is to decide whether there exists a truth assignment that satisfies all clauses of the formula. The relation between the quality of any two truth assignments and their Hamming distance is formalised. This allows modelling the expe ..."
Abstract
 Add to MetaCart
(Show Context)
Given a boolean propositional formula the satisfiability problem is to decide whether there exists a truth assignment that satisfies all clauses of the formula. The relation between the quality of any two truth assignments and their Hamming distance is formalised. This allows modelling the expected runtime of mutationselection evolutionary algorithms, including various forms of selection and mutation. The algorithmic complexity of mutationselection evolutionary algorithms can be characterised and compares well with the known complexity results for the satisfiability problem.
Formal Descriptions of Real Parameter Optimisation
"... Abstract — The design of effective operators is a matter of some interest in the evolutionary computing community, and Radcliffe’s forma analysis is one notable approach to formally incorporate domain knowledge in operator design by manipulating the formal descriptions of problem domain. Since forma ..."
Abstract
 Add to MetaCart
(Show Context)
Abstract — The design of effective operators is a matter of some interest in the evolutionary computing community, and Radcliffe’s forma analysis is one notable approach to formally incorporate domain knowledge in operator design by manipulating the formal descriptions of problem domain. Since formal description is the key issue that affects the effectiveness of derived operator, this paper examines the concepts of Dedekind Cut and Isodedekind Cut introduced by Surry. Though they serve as very useful descriptions of the continuous domain, they have not been fully formalised. Some new concepts are developed or updated based on the original work and some ambiguous points (e.g. the derivation of operators with these formal descriptions) are also made clearer. A case study is also presented to illustrate the formal derivation of concrete operators with some predefined operator templates. I.