Thuật toán Jaya được cải tiến mạnh mẽ để tối ưu hóa hiệu quả các vấn đề số và kỹ thuật

Soft Computing - Tập 26 - Trang 5315-5333 - 2022
Jafar Gholami1, Mohamad Reza Kamankesh2, Somayeh Mohammadi3,4, Elahe Hosseinkhani3, Somayeh Abdi5
1Department of Computer Engineering, Kermanshah Science and Research Branch, Islamic Azad University, Kermanshah, Iran
2Department of Computer Engineering, Borujerd Branch, Islamic Azad University, Lorestan, Iran
3Department of Computer Engineering, Kermanshah Branch, Islamic Azad University, Kermanshah, Iran
4Department of Mathematics and Computer Science, Freie Universität Berlin, Berlin, Germany
5Department of Computer Engineering, Eslam_Abade_Gharb Branch, Islamic Azad University, Eslamabad-e Gharb, Iran

Tóm tắt

Trong một thập kỷ qua, quy mô và độ phức tạp của các vấn đề thế giới thực đã gia tăng đáng kể, yêu cầu các công cụ hiệu quả hơn. Các thuật toán metaheuristic lấy cảm hứng từ thiên nhiên đã chứng tỏ là một công cụ hứa hẹn để giải quyết những vấn đề như vậy nhờ vào hiệu suất của chúng trong nhiều lĩnh vực khác nhau. Thuật toán JAYA là một thuật toán dựa trên quần thể mới có thể cung cấp kết quả đáng tin cậy. Điều này là do nó không cần bất kỳ tham số nào khác ngoài kích thước quần thể và số lần lặp tối đa. Mặc dù nhận được phản hồi tích cực, thuật toán này cần được điều chỉnh để chứng kiến hiệu quả hơn nữa. Bài báo này nhằm sửa đổi phiên bản gốc của Jaya để trình bày phiên bản hiệu suất cao được gọi là Jaya cải tiến mạnh mẽ (PEJAYA). Nói cách khác, phương pháp cập nhật vị trí trong Jaya được điều chỉnh để nâng cao khả năng hội tụ và tìm kiếm. Cách tiếp cận này được đánh giá thông qua việc giải quyết 20 hàm chuẩn nổi tiếng, lựa chọn đặc trưng và các thử nghiệm thống kê. Kết quả đầu ra của thuật toán tối ưu hóa được đề xuất sau đó được đánh giá bằng cách so sánh với các thuật toán gần đây khác bao gồm thuật toán tìm kiếm quần thể (CSA), phiên bản tiêu chuẩn của JAYA, tối ưu hóa bầy đàn (PSO), thuật toán chuồn chuồn (DA), thuật toán tối ưu hóa châu chấu (GOA), tối ưu hóa đêm (MFO), và thuật toán sóng sin-cos (SCA). Giải quyết một vấn đề thực tế là cách khác để kiểm tra hiệu quả của cách tiếp cận này so với các công trình đã công bố khác. Việc thoát khỏi cực tiểu cục bộ một cách nhanh chóng, sự hội tụ vượt trội và tính ổn định cho thấy rằng cách tiếp cận đề xuất là một công cụ rất mạnh có thể được sử dụng trong nhiều tình huống tối ưu hóa khác nhau.

Từ khóa

#thuật toán JAYA #tối ưu hóa #heuristics #cải tiến #vấn đề kỹ thuật

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