Search Results - subject:"Evolutionary computation"

Genetic Algorithms for Multi-objective Optimization: Application to a Multi-reservoir System in the Chi River Basin, Thailand

Kumphon, Bungon - In: Water Resources Management 27 (2013) 12, pp. 4369-4378

The multi-objective genetic algorithm is applied to determine the optimal operation of a multi-reservoir system in the Chi River Basin, Thailand. Two competing objective functions are considered; dam release and dam storage. The predicted values for the release and storage needed are mostly lower...

Persistent link: https://www.econbiz.de/10010794117

Improving differential evolution through a unified approach

Padhye, Nikhil; Bhardawaj, Piyush; Deb, Kalyanmoy - In: Journal of Global Optimization 55 (2013) 4, pp. 771-799

Only a few attempts in past have been made in adopting a unified outlook towards different paradigms in evolutionary … computation (EC). The underlying motivation of these studies was aimed at gaining better understanding of evolutionary methods … direction for improving an evolutionary paradigm for a task-specific. This paper recollects the ‘Unified Theory of Evolutionary …

Persistent link: https://www.econbiz.de/10010994117

The selective pickup and delivery problem: Formulation and a memetic algorithm

Ting, Chuan-Kang; Liao, Xin-Lan - In: International Journal of Production Economics 141 (2013) 1, pp. 199-211

The pickup and delivery problem addresses the real-world issues in logistic industry and establishes an important category of vehicle routing problems. The problem is to find the shortest route to collect and distribute commodities under the assumption that the total supply and the total demand...

Persistent link: https://www.econbiz.de/10010594377

Costly information and the evolution of self-organization in a small, complex economy

Wilson, James; Hill, J.; Kersula, M.; Wilson, C.L.; … - In: Journal of Economic Behavior & Organization 90 (2013) S, pp. 76-76

The core idea of evolution is that order in living systems emerges from a simple process of variation and selection. In biological systems we usually understand the source of variation as best described by the mechanisms of genetics. If human social systems are evolutionary systems, however, it...

Persistent link: https://www.econbiz.de/10010678983

Hyper-heuristic : a survey of the state of the art

Burke, Edmund K.; Gendreau, Michel; Hyde, Matthew; … - In: Journal of the Operational Research Society : OR 64 (2013) 12, pp. 1695-1724

Persistent link: https://www.econbiz.de/10010228343

Costly information and the evolution of self-organization in a small, complex economy

Wilson, James; Hill, J.; Kersula, M.; Wilson, C. L.; … - In: Journal of economic behavior & organization : JEBO 90 (2013), pp. 76-93

Persistent link: https://www.econbiz.de/10010198215

A literature review on the application of evolutionary computing to credit scoring

Marqués, A. I.; García Marzá, V. Domingo; Sánchez, J. S. - In: Journal of the Operational Research Society : OR 64 (2013) 9, pp. 1384-1399

Persistent link: https://www.econbiz.de/10009788624

An efficient Differential Evolution based algorithm for solving multi-objective optimization problems

Ali, Musrrat.; Siarry, Patrick; Pant, Millie. - In: European Journal of Operational Research 217 (2012) 2, pp. 404-416

In the present study, a modified variant of Differential Evolution (DE) algorithm for solving multi-objective optimization problems is presented. The proposed algorithm, named Multi-Objective Differential Evolution Algorithm (MODEA) utilizes the advantages of Opposition-Based Learning for...

Persistent link: https://www.econbiz.de/10010871204

Differential Evolution algorithm with Separated Groups for multi-dimensional optimization problems

Piotrowski, Adam P.; Napiorkowski, Jaroslaw J.; Kiczko, Adam - In: European Journal of Operational Research 216 (2012) 1, pp. 33-46

The classical Differential Evolution (DE) algorithm, one of population-based Evolutionary Computation methods, proved …

Persistent link: https://www.econbiz.de/10010574180

Markov chain analysis of genetic algorithms applied to fitness functions perturbed concurrently by additive and multiplicative noise

Nakama, Takehiko - In: Computational Optimization and Applications 51 (2012) 2, pp. 601-622

Persistent link: https://www.econbiz.de/10010998365