【正文】
m can be useful to support the guidepath system selection process. After choosing an appropriate type of guidepath system, the designer can use a suitable (mathematical) model to obtain the best possible guidepath system. In practice, conventional guidepath systems can be seen regularly in warehouses and distribution centers (De Koster et al., 2021)。 中英文資料 4 附錄Ⅳ 英文原文 Introduction Vehiclebased internal transport systems using automated guided vehicles (AGVs) are monly used in facilities such as manufacturing plants, warehouses, distribution centers and transshipment terminals. They are referred to as automated guided vehicle systems (AGVSs). Fig. 1 gives an example of such an AGVS in a distribution center of puter hard and software (De Koster et al., 2021), in which guided vehicles transport (pallet) loads between locations, . from receiving lanes to storage areas, and from storage areas to shipping lanes. The design and control processes of an AGVS involve many issues. The main ones are: guidepath design, estimating the number of vehicles required (or determining vehicle requirements), vehicle scheduling, idlevehicle positioning, battery management, vehicle routing and deadlock resolution. They belong to different levels of the decisionmaking process. The guidepath design can be seen as a problem at strategic level. The decision at this 中英文資料 5 stage has a strong impact on decisions at other levels. Issues at tactical level include estimating the number of vehicles, scheduling vehicle (vehicle scheduling decision may belong to both tactical and operational levels), positioning idle vehicles and, managing batterycharging scheme. Finally, vehicle routing, deadlock resolution (and prevention) problems are