Differential evolution and differential ant-stigmergy on dynamic optimisation problems
نویسندگان
چکیده
Many real-world optimisation problems are of dynamic nature, requiring an optimisation algorithm which is able to continuously track a changing optimum over time. To achieve this, we propose two population-based algorithms for solving dynamic optimisation problems (DOPs) with continuous variables: the self-adaptive differential evolution algorithm (jDE) and the differential ant-stigmergy algorithm (DASA). The performances of the jDE and the DASA are evaluated on the set of well-known benchmark problems provided for the special session on Evolutionary Computation in Dynamic and Uncertain Environments. We analyse the results for five algorithms presented by using the non-parametric statistical test procedure. The two proposed algorithms show a consistently superior performance over other recently proposed methods. The results show that both algorithms are appropriate candidates for DOPs.
منابع مشابه
A performance comparison of ant stigmergy and differential evolution for numerical optimization
The Multilevel Ant Stigmergy Algorithm (MASA) is a new approach to solving multi-parameter problems based on stigmergy, a type of collective work that can be observed in nature. In this paper we evaluate the performance of MASA regarding its applicability as numerical optimization techniques. The evaluation is performed with several widely used benchmarks functions, as well as on an industrial ...
متن کاملReal-parameter Optimization Using Stigmergy
This paper describes the so-called Differential Ant-Stigmergy Algorithm (DASA), which is an extension of the Ant-Colony Optimization for continuous domain. A performance study of the DASA on a benchmark of real-parameter optimization problems is presented. The DASA is compared with a number of evolutionary optimization algorithms including covariance matrix adaptation evolutionary strategy, dif...
متن کاملThe Multilevel Ant Stigmergy Algorithm for Numerical Optimization
The Multilevel Ant Stigmergy Algorithm (MASA) is a new approach to solving multi-parameter problems based on stigmergy, a type of collective work that can be observed in nature. In this paper we evaluate the performance of MASA regarding its applicability as numerical optimization techniques. The evaluation is performed with several widely used benchmarks functions, as well as on an industrial ...
متن کاملHigh-dimensional real-parameter optimization using the differential ant-stigmergy algorithm
Purpose – The purpose of this paper is to present an algorithm for global optimization of high-dimensional real-parameter cost functions. Design/methodology/approach – This optimization algorithm, called differential ant-stigmergy algorithm (DASA), based on a stigmergy observed in colonies of real ants. Stigmergy is a method of communication in decentralized systems in which the individual part...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
- Int. J. Systems Science
دوره 44 شماره
صفحات -
تاریخ انتشار 2013