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

【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)格的方式從國外進口商品,這與消費者小批量、個性化、實時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還能快速滿足消費者的需求,建立配送中心并保持合理的庫存就顯得尤為重要。聯(lián)合采購(Joint Replenishment,JR)策略是一種有效的成本控制手段,而在配送中心建設運作中,選址、庫存和配送(location,inventory,and delivery,LID)都是非常關鍵的決策要素�；贘R策略考慮配送中心選址、庫存、配送(JR-LID)協(xié)同優(yōu)化研究應用價值更高,但是設計高效、穩(wěn)定的高精度算法非常有挑戰(zhàn)。本文設計了一種改進的果蠅優(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,對基本的果蠅優(yōu)化算法進行兩點改進,在算法視覺搜索階段,利用果蠅的群體協(xié)作,選擇具有更好適應度值的果蠅個體朝向新位置飛行,而適應度值差的果蠅個體在搜索空間中隨機飛行;此外,加入一個隨機擾動因子,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,則采用擾動的方式改變對應果蠅的位置,以跳出局部最優(yōu)解。通過18個標準測試函數(shù)驗證了IFOA的性能。其次,將IFOA用于求解典型的聯(lián)合采購問題(JR problem,JRP),該問題為NP-hard問題。對比算例結果證實明IFOA獲得的結果優(yōu)于目前最好的智能算法。最后,討論了在三階段供應鏈網(wǎng)絡下考慮JR策略的配送中心“選址-庫存-配送”協(xié)同優(yōu)化模型求解問題。設計基于IFOA的求解算法,從而確定優(yōu)化的配送中心數(shù)量、建設位置、聯(lián)合訂貨策略和配送作業(yè)方案。通過算例和敏感性分析可為企業(yè)配送中心運營管理提供決策參考,同時通過擴展算例的求解進一步驗證了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.
【學位授予單位】：華中科技大學
【學位級別】：碩士
【學位授予年份】：2016
【分類號】：F274;F224

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本文編號：1614582