کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
392088 664667 2015 27 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Memetic binary particle swarm optimization for discrete optimization problems
ترجمه فارسی عنوان
بهینه سازی ذرات دودویی ذرات برای مشکلات بهینه سازی گسسته
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
چکیده انگلیسی

In recent decades, many researchers have been interested in algorithms inspired by the observation of natural phenomena to solve optimization problems. Among them, meta-heuristic algorithms have been extensively applied in continuous (real) and discrete (binary) search spaces. Such algorithms are appropriate for global searches because of their global exploration and local exploitation abilities. In this study, a memetic binary particle swarm optimization (BPSO) scheme is introduced based on hybrid local and global searches in BPSO. The algorithm, binary hybrid topology particle swarm optimization (BHTPSO), is used to solve the optimization problems in the binary search spaces. In addition, a variant of the proposed algorithm, binary hybrid topology particle swarm optimization quadratic interpolation (BHTPSO-QI), is proposed to enhance the global searching capability. These algorithms are tested on two set of problems in the binary search space. Several nonlinear high-dimension functions and benchmarks for the 0–1 multidimensional knapsack problem (MKP) are employed to evaluate their performances. Their results are compared with some well-known modified binary PSO and binary gravitational search algorithm (BGSA). The experimental results showed that the proposed methods improve the performance of BPSO in terms of convergence speed and solution accuracy.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Information Sciences - Volume 299, 1 April 2015, Pages 58–84
نویسندگان
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