隨著溫室效應的加劇，全球氣溫屢創新高，嚴重影響生態、社會、經濟、健康各方面，其中運輸是主要的溫室氣體排放者之一，因此各國政府陸續推廣電動車以達到減少排放之目的。對低溫物流業者來說，由於要保持溫度以避免產品品質之耗損，車輛比一般常溫車輛更消耗能源。當業者欲導入電動車取代傳統物流車進行配送時，所安排之派送路線，需考慮車輛之充電需求。本研究的目的是提出一個數學模型，旨在最小化與低溫物流電動汽車路線問題相關的運輸成本。限制式中考慮包括車容量限制及補電策略，並計算產品在運輸過程中的品質損壞程度。最後，通過一個案例來驗證所發展的模型之可行性。對於具有不同複雜程度的各種情境，所提出的模型被證明可以在可接受的品質水準下有效改善結果。在行駛距離方面可以改善13%至45%的幅度，運輸成本方面可以改善19%至35%的幅度，總時間方面可以改善1%至38%的幅度，驗證本研究模型的有效性。最後輔以所選擇的三項影響產品品質之因子進行敏感度分析，探討各因子不同水準對運輸成本與品質損壞程度的影響，根據敏感度分析的結果顯示，對於搬運速率、行駛速度和氣溫溫度三個影響產品品質之因子，溫度和搬運速率對產品品質有顯著影響。換言之，當氣溫較低時，產品保持在較好的品質水準。但是當溫度升至 25 至 30 攝氏溫度之間時，產品的最低品質水準分別只有為 48% 和 33%。當搬運速率從75 kg/min提高到150 kg/min時，產品的平均品質水準提高了6%，最低品質水準從61%提高到77%。該模型可作為低溫物流企業欲採用電動物流車進行物流運輸的決策依據。

The relentless, continuing climate change and global warming, increasing occurrences and intensification of extreme events, and the ensuing losses and damage are affecting the global economy, society, and individuals. The transportation sector is one of the largest contributors to anthropogenic greenhouse gas emissions. Governments of various countries have been promoting electric vehicles to achieve the goal of reducing emissions. Since it is necessary to maintain the temperature of some products being delivered to avoid deterioration of product quality, an electric vehicle would consume more energy than a conventional vehicle during transportation of products. When a company plans to adopt electric vehicles to replace conventional vehicles for the delivery of products, the charging requirements of these vehicles must be taken into consideration when determining the scheduled delivery route.
The aim of this study is to present a mathematical model intended to minimize the transportation costs related to the low-temperature logistics electric vehicle routing problem. Among the constraints, there are limited vehicle freight capacities and partial recharging, and the quality decay of the product during transportation. Finally, a case is used to verify the feasibility of the developed model. For various scenarios with different degrees of complexity, the proposed model was shown to effectively improve the results under acceptable quality levels. The driving distance was improved by 13% to 45%; the transportation cost was improved by 19% to 35%, and the total time was improved by 1% to 38%. Finally, based on statistical analysis, for the unloading rate, driving speed, and outside temperature three factors, temperature and unloading rate significantly impacted product quality. That is, when the outside temperature was low, the product was maintained at a better quality level. But when the temperature rose to between 25 and 30 degrees Celsius, the minimum quality level of the product was only 48% and 33%, respectively. When the unloading rate was increased from 75 kg/min to 150 kg/min, the average quality level of the product increased by 6%, and the minimum quality level increased from 61% to 77%. The proposed model could serve as a decision basis for low-temperature logistics enterprises when adopting electric vehicles for logistics transportation.

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