Quadratic assignment problems

Bài viết Tối ưu bố trí cơ sở vật chất trên mặt bằng công trình xây dựng sử dụng thuật toán lai ghép kiến sư tử (ALO) đề xuất một thuật toán mới lai ghép giữa phương pháp đột biến và trao đổi chéo, phương pháp lựa chọn cạnh tranh (Tournament selection), phương pháp học dựa trên sự đối diện (Opposition-based learning) với thuât toán cải tiến (IALO) dựa trên thuật toán Ant Lion Optimizer (ALO) để giải quyết vấn đề (Quadratic Assignment Problems – QAP) tối ưu hóa bố trí cơ sở vật chất trên mặt bằng xây dựng tìm ra một kết quả tối ưu nhất trong khoảng thời gian ngắn nhất.

10p viironman 02-06-2023 9 3   Download

In this paper, a revised version of the discrete particle swarm optimization algorithm is proposed for solving Quadratic Assignment Problems (QAP). Instead of using the general velocity and position update procedures in particle swarm optimization algorithms, four different possible positions are found out for each particle and the best among them is accepted as the updated position.

18p toritori 11-05-2020 10 0   Download

The performance of the proposed approach has been tested on several sets of instances from the data set of QAP and the results obtained have shown the effective performance of the proposed algorithm in improving several solutions of QAP in reasonable time. Afterwards, the proposed approach is compared with other recent methods in the literature review. Based on the computation results, the proposed hybrid approach outperforms the other methods.

22p toritori 11-05-2020 27 3   Download

In this article, a novel derivative-free (DF) surrogate-based trust region optimization approach is proposed. In the proposed approach, quadratic surrogate models are constructed and successively updated. The generated surrogate model is then optimized instead of the underlined objective function over trust regions. Truncated conjugate gradients are employed to find the optimal point within each trust region. The approach constructs the initial quadratic surrogate model using few data points of order O(n), where n is the number of design variables.

10p trinhthamhodang1 16-11-2019 31 2   Download

In this paper, we propose a new genetic encoding for well known Quadratic Assignment Problem (QAP). The new encoding schemes are implemented with appropriate objective function and modified genetic operators. The numerical experiments were carried out on the standard QAPLIB data sets known from the literature. The presented results show that in all cases proposed genetic algorithm reached known optimal solutions in reasonable time.

14p vinguyentuongdanh 19-12-2018 38 1   Download

A multi-goal layout problem may be formulated as a Quadratic Assignment model, considering multiple goals (or factors), both qualitative and quantitative in the objective function. The facilities layout problem, in general, varies from the location and layout of facilities in manufacturing plant to the location and layout of textual and graphical user interface components in the human–computer interface. In this paper, we propose two alternate mathematical approaches to the single-objective layout model.

22p vinguyentuongdanh 20-12-2018 33 0   Download