Integrated treatment planning for cancer patients has high importance in intensity modulated radiation therapy (IMRT). Direct aperture optimization (DAO) is one of the prominent approaches used in recent years to attain this goal. Considering a set of beam directions, DAO is an integrated approach to optimize the intensity and leaf position of apertures in each direction. In this paper, first, ...

A mammoth undertaking: harnessing insight from functional ecology to shape de-extinction priority setting Douglas J. McCauley*, Molly Hardesty-Moore, Benjamin S. Halpern and Hillary S. Young Department of Ecology, Evolution, and Marine Biology, University of California, Santa Barbara, CA 93106, USA; Bren School of Environmental Science & Management, University of California, Santa Barbara, CA 9...

Differential Evolution (DE) is a powerful optimization procedure that self-adapts to the search space, although DE lacks diversity and sufficient bias in the mutation step to make efficient progress on nonseparable problems. We present an enhancement to Differential Evolution that introduces greater diversity. The new DE approach demonstrates fast convergence towards the global optimum and is h...

The Differential Evolution (DE) is a well known Evolutionary Algorithm (EA), and is popular for its simplicity. Several novelties have been proposed in research to enhance the performance of DE. This paper focuses on demonstrating the performance enhancement of DE by implementing some of the recent ideas in DE’s research viz. Dynamic Differential Evolution (dDE), Multiple Trial Vector Different...

Grid computing is the recently growing area of computing that share data, storage, computing across geographically dispersed area. This paper proposes a novel fuzzy approach using Differential Evolution (DE) for scheduling jobs oncomputational grids. The fuzzy based DE generatesan optimal plan to complete the jobs within a minimum period of time. We evaluate the performance of the proposed fuzz...

Resumen. Este trabajo presenta una modificación del algoritmo de Hooke-Jeeves implementado en variantes de Evolución Diferencial para resolver problemas de optimización con restricciones. El algoritmo de Hooke-Jeeves promueve una mejor exploración y explotación en zonas prometedoras para encontrar mejores soluciones. El algoritmo de Hooke-Jeeves modificado es implementado en 4 variantes de Evol...

Differential Evolution (DE) is a random search algorithm used for function optimization basing on population evolution. It has been proved effective and efficient through years of studies. Among three evolutionary operations, the mutation scheme is believed to have high relation to convergence and diversity during the evolution process. This paper is going to introduce a modified differential e...

Differential Evolution (DE) is a simple but powerful evolutionary optimization algorithm with many successful applications. In this paper we propose Differential Evolution for Multiobjective Optimization (DEMO) – a new approach to multiobjective optimization based on DE. DEMO combines the advantages of DE with the mechanisms of Paretobased ranking and crowding distance sorting, used by state-of...

One of the most significant and effective criteria in the process of cutting dimensional rocks using the gang saw is the maximum energy consumption rate of the machine, and its accurate prediction and estimation can help designers and owners of this industry to achieve an optimal and economic process. In the present research work, it is attempted to study and provide models for predicting the m...

Differential Evolution (DE), proposed by Storn and Price [1,2] is a stochastic population-based search method. It exhibits excellent capability in solving a wide range of optimization problems with different characteristics from several fields and many real-world application problems [3]. Similar to all other Evolutionary algorithms (EAs), the evolutionary process of DE uses mutations, crossove...