In this piece of research, genetic algorithms are put forward for solving the HIP game. The proposed parallel approach manipulates candidate solutions via mutation and selection; no crossover has been employed. The population is limited to one candidate solution per generation, thus keeping the comp
A C3I Parallel Benchmark Based on Genetic Algorithms—Implementation and Performance Analysis
✍ Scribed by Subburajan Ponnuswamy; Minesh B. Amin; Rakesh Jha; David A. Castañon
- Publisher
- Elsevier Science
- Year
- 1997
- Tongue
- English
- Weight
- 305 KB
- Volume
- 47
- Category
- Article
- ISSN
- 0743-7315
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✦ Synopsis
As part of the ongoing effort in creating a parallel benchmark suite for C 3 I (command, control, communication, and intelligence) applications, we implemented an important C 3 I application, the decision support systems (DSS), using a genetic algorithmic approach. In this paper, we present the structure and characteristics of the DSS application and its suitability for solving under an evolutionary computing framework. We discuss many parallel formulations of the DSS and an efficient and scalable implementation on various parallel platforms. In addition to the timing analysis, we also study the scalability of various architectures for this C 3 I application. It should be noted that certain choices made in the formulation and implementation of this problem are dictated by the requirements of the benchmark.
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