本文選題：易腐食品 + 生產(chǎn)調(diào)度�。� 參考：《系統(tǒng)工程理論與實(shí)踐》2017年01期

【摘要】：為減少易腐食品在生產(chǎn)配送過(guò)程中的價(jià)值損耗,通常按訂單確定的交貨期合理組織生產(chǎn)并立即配送.為此,針對(duì)多品種易腐食品的集成生產(chǎn)-配送問(wèn)題,考慮實(shí)際配送過(guò)程中路網(wǎng)交通的時(shí)變特性,建立了以系統(tǒng)總成本最小為目標(biāo)、帶時(shí)間窗的易腐食品集成生產(chǎn)-配送問(wèn)題優(yōu)化模型.根據(jù)該模型特點(diǎn)設(shè)計(jì)了一種混合遺傳算法,并通過(guò)數(shù)值算例驗(yàn)證了所提模型和算法的有效性.結(jié)果表明,路網(wǎng)的時(shí)變特性顯著影響客戶(hù)服務(wù)水平,優(yōu)化投入配送的車(chē)輛數(shù)可有效降低系統(tǒng)總成本和易腐食品的價(jià)值損耗.
[Abstract]:In order to reduce the value loss of perishable food in the production and distribution process, the production is usually organized and delivered immediately according to the delivery date determined by the order. In order to solve the problem of integrated production-distribution of various perishable foods, considering the time-varying characteristics of road network traffic in the actual distribution process, the aim of this paper is to minimize the total cost of the system. An optimal model for integrated production and distribution of perishable food with time window. According to the characteristics of the model, a hybrid genetic algorithm is designed, and the validity of the proposed model and algorithm is verified by numerical examples. The results show that the time-varying characteristics of the road network significantly affect the level of customer service, and the optimization of the number of vehicles put into distribution can effectively reduce the total cost of the system and the value loss of perishable food.
【作者單位】： 西南交通大學(xué)經(jīng)濟(jì)管理學(xué)院物流與應(yīng)急管理研究所;
【基金】：國(guó)家自然科學(xué)基金重大研究計(jì)劃培育項(xiàng)目(90924012);國(guó)家自然科學(xué)基金面上項(xiàng)目(71672154) 教育部人文社會(huì)科學(xué)研究規(guī)劃基金項(xiàng)目(16YJA630038)~~
【分類(lèi)號(hào)】：F274

【相似文獻(xiàn)】

相關(guān)期刊論文 前3條

1 衛(wèi)斐;王喜成;;基于線(xiàn)性規(guī)劃博弈的供應(yīng)鏈配送問(wèn)題[J];經(jīng)濟(jì)數(shù)學(xué);2009年04期

2 張凱;席一凡;;改進(jìn)的TSP算法求解供應(yīng)鏈一對(duì)多配送問(wèn)題[J];科技管理研究;2011年06期

3 沈國(guó)軍;;基于多目標(biāo)混合遺傳算法的人力資源配置模型構(gòu)建[J];統(tǒng)計(jì)與決策;2013年21期

相關(guān)碩士學(xué)位論文 前1條

1 朱沛;基于混合遺傳算法的汽車(chē)企業(yè)營(yíng)銷(xiāo)資源分配策略研究[D];武漢理工大學(xué);2012年

，

本文編號(hào)：1839008