本文選題：果蠅優(yōu)化算法　切入點(diǎn)：聯(lián)合采購(gòu)　出處：《華中科技大學(xué)》2016年碩士論文　論文類型：學(xué)位論文

【摘要】：為有效降低成本,跨境電商企業(yè)需要盡可能采用大批量、少規(guī)格的方式從國(guó)外進(jìn)口商品,這與消費(fèi)者小批量、個(gè)性化、實(shí)時(shí)化需求之間的矛盾非常突出。為緩解這一矛盾,有效降低成本的同時(shí)還能快速滿足消費(fèi)者的需求,建立配送中心并保持合理的庫(kù)存就顯得尤為重要。聯(lián)合采購(gòu)(Joint Replenishment,JR)策略是一種有效的成本控制手段,而在配送中心建設(shè)運(yùn)作中,選址、庫(kù)存和配送(location,inventory,and delivery,LID)都是非常關(guān)鍵的決策要素�；贘R策略考慮配送中心選址、庫(kù)存、配送(JR-LID)協(xié)同優(yōu)化研究應(yīng)用價(jià)值更高,但是設(shè)計(jì)高效、穩(wěn)定的高精度算法非常有挑戰(zhàn)。本文設(shè)計(jì)了一種改進(jìn)的果蠅優(yōu)化(Improved Fruit Fly Optimization,IFOA)算法,并用于求解配送中心JR-LID協(xié)同優(yōu)化難題。首先,對(duì)基本的果蠅優(yōu)化算法進(jìn)行兩點(diǎn)改進(jìn),在算法視覺(jué)搜索階段,利用果蠅的群體協(xié)作,選擇具有更好適應(yīng)度值的果蠅個(gè)體朝向新位置飛行,而適應(yīng)度值差的果蠅個(gè)體在搜索空間中隨機(jī)飛行;此外,加入一個(gè)隨機(jī)擾動(dòng)因子,如果本次迭代的最優(yōu)解比迄今為止已發(fā)現(xiàn)的最優(yōu)解差,則采用擾動(dòng)的方式改變對(duì)應(yīng)果蠅的位置,以跳出局部最優(yōu)解。通過(guò)18個(gè)標(biāo)準(zhǔn)測(cè)試函數(shù)驗(yàn)證了IFOA的性能。其次,將IFOA用于求解典型的聯(lián)合采購(gòu)問(wèn)題(JR problem,JRP),該問(wèn)題為NP-hard問(wèn)題。對(duì)比算例結(jié)果證實(shí)明IFOA獲得的結(jié)果優(yōu)于目前最好的智能算法。最后,討論了在三階段供應(yīng)鏈網(wǎng)絡(luò)下考慮JR策略的配送中心“選址-庫(kù)存-配送”協(xié)同優(yōu)化模型求解問(wèn)題。設(shè)計(jì)基于IFOA的求解算法,從而確定優(yōu)化的配送中心數(shù)量、建設(shè)位置、聯(lián)合訂貨策略和配送作業(yè)方案。通過(guò)算例和敏感性分析可為企業(yè)配送中心運(yùn)營(yíng)管理提供決策參考,同時(shí)通過(guò)擴(kuò)展算例的求解進(jìn)一步驗(yàn)證了IFOA算法的有效性和穩(wěn)定性。
[Abstract]:In order to effectively reduce costs, cross-border e-commerce enterprises need to import goods from abroad in as large a quantity and less specifications as possible. This contradiction with consumers' small volume, personalized and real-time needs is very prominent. It is very important to set up distribution center and maintain reasonable inventory while effectively reducing cost and meeting the needs of consumers. Joint Replenishment JRR is an effective means of cost control, but in the construction and operation of distribution center, JRR is an effective means of cost control. Location, inventory and distribution inventory and delivery LIDs are all very critical elements of decision making. Considering distribution center location, inventory, and distribution JR-LID-based collaborative optimization research is more valuable, but the design is more efficient. The stable high precision algorithm is very challenging. In this paper, an improved Fruit Fly optimization algorithm is designed, which is used to solve the problem of JR-LID cooperative optimization in distribution center. Firstly, two improvements are made to the basic Drosophila optimization algorithm. In the visual search phase of the algorithm, the individual flies with a better fitness value are selected to fly towards a new position, while the individuals with poor fitness value fly randomly in the search space, using the collaboration of the drosophila population. If a random perturbation factor is added, if the optimal solution of this iteration is different from that found so far, the position of the corresponding fruit fly will be changed by perturbation. In order to jump out of the local optimal solution, the performance of IFOA is verified by 18 standard test functions. Secondly, IFOA is used to solve a typical joint procurement problem, which is a NP-hard problem. The comparison of the results of an example shows that the results obtained by IFOA are superior to those obtained by the best intelligent algorithm. This paper discusses the solution of the "location-stock-distribution" collaborative optimization model of distribution center considering Jr strategy in three-stage supply chain network. A solution algorithm based on IFOA is designed to determine the number of optimized distribution centers and the construction location. Through the example and sensitivity analysis, it can provide the decision reference for the enterprise distribution center operation management. At the same time, the validity and stability of the IFOA algorithm are further verified by solving the extended example.
【學(xué)位授予單位】：華中科技大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2016
【分類號(hào)】：F274;F224

【參考文獻(xiàn)】

相關(guān)期刊論文 前4條

1 于博;;改進(jìn)的果蠅優(yōu)化算法在城市物流配送中心選址中的應(yīng)用[J];山東農(nóng)業(yè)大學(xué)學(xué)報(bào)(自然科學(xué)版);2015年04期

2 劉志雄;王雅芬;張煜;;多種群果蠅優(yōu)化算法求解自動(dòng)化倉(cāng)庫(kù)揀選作業(yè)調(diào)度問(wèn)題[J];武漢理工大學(xué)學(xué)報(bào);2014年03期

3 韓俊英;劉成忠;;基于細(xì)菌趨化的果蠅優(yōu)化算法[J];計(jì)算機(jī)應(yīng)用;2013年04期

4 王戰(zhàn)權(quán),楊東援,汪超;配送中心選址的遺傳算法研究[J];物流技術(shù);2001年03期

相關(guān)碩士學(xué)位論文 前1條

1 賀靖;基于差分進(jìn)化算法的聯(lián)合補(bǔ)貨模型研究[D];華中科技大學(xué);2010年

，

本文編號(hào)：1614582