本文選題：蜂群算法 + 農(nóng)產(chǎn)品基地��； 參考：《控制工程》2016年07期

【摘要】：農(nóng)產(chǎn)品的生產(chǎn)與供應(yīng)對成本與供貨時間要求極高,提出一種增強的蜂群算法來優(yōu)化農(nóng)產(chǎn)品基地的多基地、多目標供應(yīng)鏈優(yōu)化問題。首先,將蜂群中適應(yīng)度值最高的地點選為目標地點,將其作為鄰域搜索的輸入?yún)?shù),并為目標地點分配較多的搜索蜂,為非目標地點分配較少的搜索蜂;然后,經(jīng)過一定次數(shù)的迭代搜索后,放棄其中改進不明顯的地點,以此避免陷入局部最優(yōu)并提高收斂速度;最終,將增強的蜂群算法結(jié)合農(nóng)產(chǎn)品供應(yīng)鏈進行實驗與分析,獲得了較好的優(yōu)化效果。對比實驗結(jié)果表明,算法獲得較多的總成本與供貨時間的帕累托最優(yōu)解,可提供較多的供應(yīng)鏈網(wǎng)絡(luò)配置方案,同時,算法的魯棒性與計算效率也具有優(yōu)勢。
[Abstract]:The production and supply of agricultural products require very high cost and supply time. An enhanced bee colony algorithm is proposed to optimize the multi-base and multi-objective supply chain optimization of agricultural products. First of all, the most suitable location in the colony is chosen as the input parameter of neighborhood search, and more search bees are assigned to the target site and fewer search bees are assigned to the non-target location. After a certain number of iterative searches, we give up the places where the improvement is not obvious, so as to avoid falling into the local optimum and improve the convergence speed. Finally, the enhanced bee colony algorithm is combined with the agricultural product supply chain to carry out experiments and analysis. A better optimization effect is obtained. The experimental results show that the algorithm can obtain more Pareto optimal solutions of total cost and supply time, and can provide more supply chain network configuration schemes. At the same time, the robustness and computational efficiency of the algorithm also have advantages.
【作者單位】： 韶關(guān)學院信息科學與工程學院;
【基金】：廣東省自然科學基金(2014A030313700) 廣東省科技計劃項目(2013B070206076) 廣東省哲學社會科學項目(GD13XGL29) 廣東省普通高校特色創(chuàng)新項目(2014KTSCX171,2014WTSCX094) 韶關(guān)市科技計劃項目(2014CX/K252)
【分類號】：F304;TP18

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本文編號：1968264