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 Using Fuzzy Clustering Chaotic-based Differential Evolution to solve multiple resources leveling in the multiple projects scheduling problem
Tác giả hoặc Nhóm tác giả: Duc-Hoc Tran; Min-Yuan Cheng and Anh-Duc Pham
Nơi đăng: Alexandria Engineering Journal; Số: 55 (2);Từ->đến trang: 1541–1552;Năm: 2016
Lĩnh vực: Kỹ thuật; Loại: Bài báo khoa học; Thể loại: Quốc tế
TÓM TẮT
Duc-Hoc Tran; Min-Yuan Cheng and Anh-Duc Pham
ABSTRACT
Project scheduling is an important part of construction project planning. Resource leveling is the process used within project scheduling to reduce fluctuations in resource usage over the period of project implementation. These fluctuations frequently create the untenable requirement of regularly hiring and firing temporary staff resources to meet short-term project needs. Construction project decision makers currently rely on experience-based methods to manage fluctuations. However, these methods lack consistency and may result in unnecessary wastage of resources or costly schedule overruns. This research introduces a novel optimization model called the Fuzzy Clustering Chaotic-based Differential Evolution for solving multiple resources leveling in the multiple projects scheduling problem (FCDE-MRLMP). The novel Fuzzy Clustering Chaotic-based Differential Evolution (FCDE) algorithm integrates fuzzy c-means clustering and chaotic techniques into the original Differential Evolution (DE) algorithm to handle complex optimization problems. The chaotic technique prevents the optimization algorithm from converging prematurely. The fuzzy c-means clustering technique acts as several multi-parent crossover operators in order to utilize population information efficiently and enhance convergence efficiency. Experiments run indicate that the proposed model obtains optimal results more reliably and efficiently than the benchmark algorithms considered. The proposed optimization model is a promising alternative approach to assist project managers to handle resource-leveling project scheduling problems effectively.
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