【摘要】：貪婪算法(Greedy algorithm)只關(guān)注當(dāng)前匹配的收益,在車貨匹配的過程中有可能出現(xiàn)集中匹配同一車型的情況,導(dǎo)致匹配的效果并不理想。對Balance算法進行改進,并應(yīng)用于車貨匹配中,提出基于改進Balance算法的車貨匹配模型(Improved Balance Vehicles and Cargos Matching Model,IBVCM)。模型引入車貨匹配平衡函數(shù)定義各車型的匹配情況,并根據(jù)車貨之間的匹配關(guān)系對函數(shù)進行修正,在為貨物選擇匹配車型時綜合考慮當(dāng)前車貨匹配的收益以及車型匹配情況兩個因素。實驗結(jié)果表明,文中所提的IBVCM模型與貪婪算法相比匹配的成功率提高13.5%,匹配的總收益提高18%。
[Abstract]:Greedy algorithm only pays attention to the current matching income. In the process of vehicle and cargo matching, it is possible to focus on matching the same vehicle, which leads to the unsatisfactory matching effect. This paper improves the balance algorithm and applies it to the vehicle and cargo matching. An improved balance vehicles and cargos matching Model (IBVCM) is proposed based on the improved balance algorithm. The model introduces vehicle and cargo matching balance function to define the matching situation of each vehicle, and modifies the function according to the matching relationship between vehicles and goods. When selecting the matching model for the goods, two factors are considered synthetically: the income of the current vehicle and cargo matching and the matching situation of the vehicle type. The experimental results show that the IBVCM model proposed in this paper increases the success rate of matching by 13.5% and the total income of matching by 18% compared with greedy algorithm.
【作者單位】： 華南師范大學(xué)經(jīng)濟與管理學(xué)院;
【基金】：廣東省科技廳軟科學(xué)研究計劃(2014A07073043) 2016年廣州市產(chǎn)學(xué)研協(xié)同創(chuàng)新重大專項
【分類號】：F252

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