排程(scheduling)問題一直是營建管理領域研究的重要課題。不論是在專案初期的可行性分析、建設中的作業時程監督，專案的排程都佔據著舉足輕重的地位。近年來有許多的有限資源排程最佳化之研究，但大多都著重於單一專案之排程問題，並沒有考慮到在多專案下之情形，本研究結合了基因演算法以及混和解交換機制，加上經驗法則中的前後調度法求解多專案有限資源調度問題(resource constrained multi-project scheduling problem, RCMPSP)，使解答符合有限資源的限制以及前後關係的條件。依據文獻案例的應用結果，本研究提出之演算法(hybrid Genetic Algorithm-Permutation Based Particle Swarm Optimization-Heuristic, hyGPH)優於之前研究所提出的多專案有限資源排程案例進行比較。其比較結果顯示本研究的最佳解與平均解均優於其他演算法，且僅需較少的目標函式呼叫次數及可求得解答。證明本研究之演算法適合用於多專案有限資源排程問題。

Scheduling has long been an important subject in the field of construction management. Project scheduling is essential not only in the pre-project planning phase but also during construction. In recent year, only limited efforts are directed to address the practical concern that resources (manpower and equipment) are often shared between multiple projects. This study intends to solve the resource constrained multi-project scheduling problem (RCMPSP) with improved effectiveness and efficiency. To achieve the goal, the present study integrates Genetic Algorithm (GA), Permutation-Based Particle Swarm Optimization (P-PSO), and the Backward-Forward Heuristic into a new scheduling system, which is called hyGPH (hybrid Genetic Algorithm-Permutation Based Particle Swarm Optimization-Heuristic). hyGPH is applied to solve two practical RCMPSP problems. The results demonstrate that hyGPH is consistently superior to other popular metaheuristics, such as GA and PSO. The advantages of hyGPH include better solution quality, i.e., shorter duration, and reduced computational efforts. Successful applications help confirm that hyGPH can be applied in practical cases.

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