Thuật toán tối ưu hóa cá voi nâng cao với việc cải thiện học ngược động và chiến lược trọng số quán tính thích nghi

Di Cao1, Yujie Xu2, Zhile Yang3, He Dong1, Xiaoping Li1
1State Key Laboratory of Digital Manufacturing Equipment and Technology, Huazhong University of Science and Technology, Wuhan 430074, China
2State Key Laboratory of ASIC and System, School of Microelectronics, Fudan University, Shanghai, 200433, China
3Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China

Tóm tắt

Tóm tắtThuật toán Tối ưu hóa Cá voi (WOA), là một thuật toán mới được đề xuất dựa trên bầy đàn, đã từng bước trở thành một phương pháp phổ biến cho các bài toán tối ưu hóa trong nhiều lĩnh vực kỹ thuật khác nhau. Tuy nhiên, WOA gặp khó khăn với việc cân bằng kém giữa thăm dò và khai thác, cũng như hội tụ sớm. Trong bài báo này, một WOA nâng cao mới (EWOA), áp dụng một học ngược động cải tiến (IDOL) và giai đoạn bao quanh con mồi thích nghi, được đề xuất để khắc phục những vấn đề này. IDOL đóng một vai trò quan trọng trong phần khởi tạo và quá trình lặp của thuật toán EWOA. Bằng cách đánh giá giải pháp tối ưu trong quần thể hiện tại, IDOL có thể chuyển đổi cách thăm dò/khai thác một cách thích nghi dựa trên chiến lược DOL và một chiến lược tìm kiếm đã được sửa đổi. Mặt khác, đối với giai đoạn bao quanh con mồi của EWOA ở phần sau của quá trình lặp, một chiến lược trọng số quán tính thích nghi được giới thiệu vào giai đoạn này để điều chỉnh vị trí của con mồi một cách thích nghi nhằm tránh rơi vào các cực địa phương. Các thí nghiệm số, với các chuẩn mực đơn cực, đa cực, lai và tổ hợp, cùng ba vấn đề kỹ thuật điển hình được sử dụng để đánh giá hiệu suất của EWOA. EWOA được đề xuất cũng được so sánh với WOA tiêu chuẩn, ba biến thể phụ của EWOA, ba thuật toán phổ biến khác, ba thuật toán tiên tiến và bốn biến thể nâng cao của WOA. Kết quả cho thấy, theo kiểm định tổng hợp Wilcoxon và kiểm định Friedman, EWOA có khả năng cân bằng giữa thăm dò và khai thác khi đối phó với tối ưu hóa toàn cầu, và nó có những lợi thế rõ rệt khi so với các thuật toán tiên tiến khác.

Từ khóa


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