کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
414048 680800 2013 10 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
A comparison of two chromosome representation schemes used in solving a family-based scheduling problem
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
پیش نمایش صفحه اول مقاله
A comparison of two chromosome representation schemes used in solving a family-based scheduling problem
چکیده انگلیسی

Meta-heuristic algorithms have been widely used in solving scheduling problems; previous studies focused on enhancing existing algorithmic mechanisms. This study advocates a new perspective—developing new chromosome (solution) representation schemes may improve the performance of existing meta-heuristic algorithms. In the context of a scheduling problem, known as permutation manufacturing-cell flow shop (PMFS), we compare the effectiveness of two chromosome representation schemes (Sold and Snew) while they are embedded in a meta-heuristic algorithm to solve the PMFS scheduling problem. Two existing meta-heuristic algorithms, genetic algorithm (GA) and ant colony optimization (ACO), are tested. Denote a tested meta-heuristic algorithm by X_Y, where X represents an algorithmic mechanism and Y represents a chromosome representation. Experiment results indicate that GA_ Snew outperforms GA_Sold, and ACO_Snew also outperforms ACO_Sold. These findings reveal the importance of developing new chromosome representations in the application of meta-heuristic algorithms.


► We study the effect of chromosome representations on the performance of GA and ACO.
► A scheduling problem (PMFS) is used as the problem context.
► Numerical experiments reveal that GA_Snew comprehensively outperforms GA_Sold.
► Numerical experiments indicate that ACO_Snew comprehensively outperforms ACO_Sold.
► This finding highlights the value of exploring new solution representation schemes.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Robotics and Computer-Integrated Manufacturing - Volume 29, Issue 3, June 2013, Pages 21–30
نویسندگان
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