越庫作業被認為是一個在供應鏈管理中能夠有效控制存貨流動的方法。在本論文中，我們探討越庫作業系統之時窗車輛指派問題。在這個模型之中，每台車輛都有時間窗的限制，且車輛數超過現有的碼頭數，此問題同時包含越庫作業系統中倉儲的容量限制。在本篇論文主要的目的是決定卡車的最佳指派，使得卡車停靠在碼頭的總運營成本和對未完成發貨的處罰成本最小化。此問題主要受三個因素影響：(1) 車輛到達和離開時間窗，(2) 碼頭間的運輸成本，(3) 越庫作業系統的總容量限制。我們提出兩個啟發法求解此問題，並配合粒子群演算法 (PSO)。實驗結果證明，該啟發式演算法比現有的禁忌搜索（TS）法在計算時間與結果上，表現均為優良，而 PSO也可在短的時間內得到近似最佳解。

In this paper, we consider a truck dock assignment problem with an operational time constraint in a crossdock where the number of trucks exceeds the number of docks available. The objective of the problem is to find an optimal truck dock assignment to minimize the sum of the total dock operational cost and the penalty cost for all the unfulfilled shipments. The problem is limited by the crossdock capacity where the cargo temporary storage. The problem feasibility is affected by three factors: the arrival and departure time windows of each truck, the operational time for the cargo shipments among the docks, and the total capacity available to the crossdock. Two heuristics are proposed in this paper for the problem. To obtain a better solution, a Particle Swarm Optimization (PSO) algorithm combined with the heuristics is also proposed. Computational experiments show that the heuristics alone perform better than an existing tabu search (TS) algorithm in terms of computation time and solution quality. The PSO algorithm also outperforms the TS algorithm when both employing the heuristics.

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