Nội dung được dịch bởi AI, chỉ mang tính chất tham khảo
Một thuật toán metaheuristic học tập cải tiến với học tập dựa trên đối lập cho bài toán lập lịch dòng chảy hoán vị
Tóm tắt
Tối ưu hóa dựa trên học tập là một trong những thuật toán metaheuristic nổi tiếng trong ngành nghiên cứu. Gần đây, nhiều thuật toán dựa trên quần thể đã được phát triển để giải quyết các vấn đề tối ưu hóa. Trong bài báo này, một phương pháp hệ số tỷ lệ ngẫu nhiên được đề xuất để sửa đổi thuật toán TLBO đơn giản. Tối ưu hóa dựa trên học tập đã được sửa đổi với thuật toán Học tập Dựa trên Đối lập được áp dụng để giải quyết Bài toán Lập lịch Dòng chảy Hoán vị với mục tiêu giảm thiểu thời gian hoàn thành. Phương pháp OBL được sử dụng để nâng cao chất lượng quần thể ban đầu và tốc độ hội tụ. PFSSP được sử dụng rộng rãi để giải quyết vấn đề lập lịch, thuộc thể loại các bài toán tối ưu NP-khó. Đầu tiên, MTLBO được phát triển để xác định hiệu quả PFSSP sử dụng quy tắc giá trị thứ tự lớn nhất dựa trên khóa ngẫu nhiên, do đó các lịch việc làm cá nhân được chuyển đổi thành các lịch rời rạc. Thứ hai, các quần thể ban đầu mới được tạo ra trong MTLBO bằng cách sử dụng cơ chế heuristics Nawaz–Enscore–Ham. Cuối cùng, khả năng khai thác cục bộ được nâng cao trong MTLBO bằng cách sử dụng các cấu trúc hoán đổi, chèn và đối xứng hiệu quả. Hiệu suất của thuật toán đề xuất được xác nhận bằng mười hàm chuẩn và bài kiểm tra thứ hạng Wilcoxon. Kết quả tính toán và các so sánh cho thấy thuật toán đề xuất vượt trội hơn trên năm tập dữ liệu nổi tiếng như Carlier, Reeves, Heller, Taillards và các hàm thử nghiệm chuẩn VRF, so với các thuật toán metaheuristic khác. Giá trị p cho thấy sự đáng kể và ưu việt của thuật toán đề xuất so với các thuật toán metaheuristic khác.
Từ khóa
#Tối ưu hóa dựa trên học tập #thuật toán metaheuristic #bài toán lập lịch dòng chảy hoán vị #OBL #PFSSPTài liệu tham khảo
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