Pareto simulated annealing for the design of experiments: illustrated by a gene expression study

• Autorzy: Sanchez P. , Glonek G. , Metcalfe A.
• Języki publikacji: EN

Abstrakty

EN

Experimental design is concerned with the problem of allocating resources within an experiment to ensure that objectives of the experiment are achieved at the minimum cost. This paper focuses on the generation of optimal or near-optimal designs for large and complex experiments where it is infeasible to carry out an exhaustive search of the design space. Optimal designs for gene expression studies, aimed at investigating the behaviour of genes, are considered, where the optimality criterion employed is Pareto optimality. We develop an adaptation of the metaheuristic method of Pareto simulated annealing to generate an approximation to the set of Pareto optimal designs for large and complex experiments. We develop algorithms that utilise response surface methodology to search systematically for the optimal values of parameters associated with Pareto simulated annealing and performance is evaluated using quality measures.

Słowa kluczowe

EN

Combinatorial optimisationx; metaheuristics; Pareto simulated annealing; Experimental designx; Gene expression study

• Wydawca: Wydawnictwo Politechniki Poznańskiej
• Czasopismo: Foundations of Computing and Decision Sciences
• Rocznik: 2012
• Tom: Vol. 37, No. 3
• Strony: 199--221
• Opis fizyczny: Bibliogr. 14 poz.

Twórcy

autor

Sanchez P.

• University of South Australia, School of Mathematics and Statistics, Mawson Lakes Campus, Mawson Lakes, South Australia, 5095, Australia

autor

Glonek G.

• University of Adelaide, School of Mathematical Sciences, Adelaide, South Australia, 5005, Australia

autor

Metcalfe A.

• University of Adelaide, School of Mathematical Sciences, Adelaide, South Australia, 5005, Australia

Bibliografia

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