Towards a characterisation of the behaviour of stochastic local search algorithms for SAT
Artificial Intelligence
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Estimation of Distribution Algorithms: A New Tool for Evolutionary Computation
Estimation of Distribution Algorithms: A New Tool for Evolutionary Computation
Using Optimal Dependency-Trees for Combinational Optimization
ICML '97 Proceedings of the Fourteenth International Conference on Machine Learning
From Recombination of Genes to the Estimation of Distributions I. Binary Parameters
PPSN IV Proceedings of the 4th International Conference on Parallel Problem Solving from Nature
PPSN IV Proceedings of the 4th International Conference on Parallel Problem Solving from Nature
Population-Based Incremental Learning: A Method for Integrating Genetic Search Based Function Optimization and Competitive Learning
Using a Markov network model in a univariate EDA: an empirical cost-benefit analysis
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
Optimising cancer chemotherapy using an estimation of distribution algorithm and genetic algorithms
Proceedings of the 8th annual conference on Genetic and evolutionary computation
Hierarchical BOA on random decomposable problems
Proceedings of the 8th annual conference on Genetic and evolutionary computation
IEEE Transactions on Evolutionary Computation
Heuristic design of cancer chemotherapies
IEEE Transactions on Evolutionary Computation
Automating the drug scheduling of cancer chemotherapy via evolutionary computation
Artificial Intelligence in Medicine
Optimising cancer chemotherapy using an estimation of distribution algorithm and genetic algorithms
Proceedings of the 8th annual conference on Genetic and evolutionary computation
An application of EDA and GA to dynamic pricing
Proceedings of the 9th annual conference on Genetic and evolutionary computation
An application of a multivariate estimation of distribution algorithm to cancer chemotherapy
Proceedings of the 10th annual conference on Genetic and evolutionary computation
The effects of mutation and directed intervention crossover when applied to scheduling chemotherapy
Proceedings of the 10th annual conference on Genetic and evolutionary computation
Hybrid Ant Colony Algorithm and Its Application on Function Optimization
ISICA '08 Proceedings of the 3rd International Symposium on Advances in Computation and Intelligence
Modeling and optimization of combined cytostatic and cytotoxic cancer chemotherapy
Artificial Intelligence in Medicine
Introducing intervention targeting into estimation of distribution algorithms
Proceedings of the 27th Annual ACM Symposium on Applied Computing
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This paper presents a methodology for using heuristic search methods to optimise cancer chemotherapy. Specifically, two evolutionary algorithms - Population Based Incremental Learning (PBIL), which is an Estimation of Distribution Algorithm (EDA), and Genetic Algorithms (GAs) have been applied to the problem of finding effective chemotherapeutic treatments. To our knowledge, EDAs have been applied to fewer real world problems compared to GAs, and the aim of the present paper is to expand the application domain of this technique.We compare and analyse the performance of both algorithms and draw a conclusion as to which approach to cancer chemotherapy optimisation is more efficient and helpful in the decision-making activity led by the oncologists.