【摘要】：隨著全球競爭的日益加劇,以客戶為中心的供應(yīng)鏈管理模式逐步取代了以生產(chǎn)和產(chǎn)品為中心的傳統(tǒng)管理模式。采購管理作為供應(yīng)鏈管理中的重要組成部分,對整條供應(yīng)鏈起到了價(jià)值創(chuàng)造以及增長的作用。企業(yè)對采購活動的有效管理不僅可以降低運(yùn)營成本,增強(qiáng)市場競爭力,而且可以保證其在快速多變的市場中處于領(lǐng)先地位。本文首先對供應(yīng)鏈管理理論中庫存管理和采購批量理論以及不確定理論進(jìn)行了綜述。總結(jié)了某營銷商所處供應(yīng)鏈的各個(gè)環(huán)節(jié)的特點(diǎn)及其自身的特點(diǎn)。分析了由于供應(yīng)鏈的不確定性導(dǎo)致商品到貨時(shí)間的不確定性,以及由到貨時(shí)間不確定引起的到貨量不確定,并將該問題轉(zhuǎn)化為不確定的到貨率處理。通過歷史數(shù)據(jù)和專家經(jīng)驗(yàn)值估計(jì),將不確定的到貨率擬合成隨機(jī)模糊變量,提出了在下游客戶訂單需求確定而訂單到貨時(shí)間不確定的情況下,如何分配該營銷商在全年多個(gè)訂購周期同時(shí)訂購多品種商品的批量,使企業(yè)得到最小化運(yùn)營成本的優(yōu)化模型。本文綜合考慮訂單的最低訂購量限制、庫存容量和流動資金的約束、必須滿足客戶需求等限制條件,基于不確定理論中的隨機(jī)模糊理論,建立了到貨時(shí)間不確定的多商品訂購批量隨機(jī)模糊優(yōu)化模型；基于不確定規(guī)劃中的期望值規(guī)劃,將含有隨機(jī)模糊變量的優(yōu)化模型轉(zhuǎn)化為隨機(jī)模糊期望值模型進(jìn)行求解。其次,針對所建立的模型,設(shè)計(jì)了模型求解的遺傳算法。在算法設(shè)計(jì)中,針對問題的特點(diǎn),設(shè)計(jì)了以商品各周期訂購量為基因段的整數(shù)染色體編碼方式；采用一種啟發(fā)式方法實(shí)現(xiàn)種群的初始化；根據(jù)染色體編碼的特點(diǎn),設(shè)計(jì)了基于基因段的均勻交叉和基因段內(nèi)的單點(diǎn)交叉算子,以及基于基因段的啟發(fā)式變異和基因段內(nèi)的互換變異算子；針對選擇算子,本文混合采用輪盤賭的選擇策略和精英選擇策略；針對不可行染色體,設(shè)計(jì)了修復(fù)策略。最后算法采用C語言編程實(shí)現(xiàn),結(jié)合企業(yè)實(shí)際部分?jǐn)?shù)據(jù),進(jìn)行了模型的仿真實(shí)驗(yàn)。算法參數(shù)實(shí)驗(yàn)包括遺傳算法的相關(guān)參數(shù)的仿真實(shí)驗(yàn),如交叉變異算子對遺傳算法性能的影響分析、遺傳算法性能與收斂性的實(shí)驗(yàn)分析、不同選擇策略的對比分析；模型參數(shù)實(shí)驗(yàn)包括對庫存容量、流動資金、調(diào)貨價(jià)格、不同折扣優(yōu)惠力度以及到貨時(shí)間的確定與否對運(yùn)營成本的影響進(jìn)行了詳細(xì)分析,最后分析調(diào)貨啟動成本和調(diào)貨可變成本對調(diào)貨總成本的影響。仿真實(shí)驗(yàn)結(jié)果驗(yàn)證了本文所建立的模型和算法的有效性及可行性。
[Abstract]:With the increasing competition in the world, the customer-centered supply chain management model gradually replaces the traditional production and product-centered management model. Procurement management, as an important part of supply chain management, plays an important role in value creation and growth of the whole supply chain. The effective management of purchasing activities can not only reduce the operating cost, enhance the market competitiveness, but also ensure that it is in a leading position in the fast changing market. In this paper, the inventory management, procurement batch theory and uncertainty theory in the theory of supply chain management are reviewed. This paper summarizes the characteristics of each link of the supply chain where a certain marketer is located and its own characteristics. In this paper, the uncertainty of arrival time and the uncertainty of arrival quantity caused by the uncertainty of supply chain are analyzed, and the problem is transformed into uncertain arrival rate. Through the historical data and expert experience value estimation, the uncertain arrival rate is combined with random fuzzy variables, and it is proposed that when the downstream customer order demand is determined and the order arrival time is uncertain, How to allocate the distributor to order the batch of multi-product at the same time in multiple ordering cycles in the whole year, so that the enterprise can get an optimal model to minimize the operating cost. Based on the stochastic fuzzy theory of uncertainty theory, this paper considers the minimum order quantity limit of order, the restriction of inventory capacity and liquidity, and so on, which must satisfy the demand of customers, and is based on the stochastic fuzzy theory of uncertainty theory. A stochastic fuzzy optimization model of multi-product ordering batch with uncertain arrival time is established. Based on the expected value programming in uncertain programming, the optimization model with random fuzzy variables is transformed into a stochastic fuzzy expected value model to solve the problem. Secondly, according to the established model, the genetic algorithm for solving the model is designed. In the algorithm design, according to the characteristics of the problem, the integer chromosome coding method based on the order quantity of each period of the commodity is designed, and a heuristic method is used to realize the initialization of the population. According to the characteristics of chromosome coding, uniform crossover based on gene segment and single point crossover operator in gene segment are designed, heuristic mutation operator based on gene segment and exchange mutation operator within gene segment are designed. For the selection operator, the roulette selection strategy and elite selection strategy are used in this paper, and the repair strategy is designed for the infeasible chromosome. Finally, the algorithm is programmed in C language and combined with the actual data of the enterprise, the simulation experiment of the model is carried out. The parameters of the algorithm include the simulation experiments of the related parameters of the genetic algorithm, such as the influence of crossover mutation operator on the performance of the genetic algorithm, the experimental analysis of the performance and convergence of the genetic algorithm, and the comparative analysis of different selection strategies. The model parameter experiment includes a detailed analysis of the impact of inventory capacity, liquidity, transfer price, different discount rates and arrival time on operating costs. Finally, the influence of start-up cost and variable cost of transfer on the total cost of transfer is analyzed. The simulation results verify the validity and feasibility of the proposed model and algorithm.
【學(xué)位授予單位】：東北大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2014
【分類號】：TP18;F274

【參考文獻(xiàn)】

相關(guān)期刊論文 前1條

1 馬士華;王福壽;;時(shí)間價(jià)格敏感型需求下的供應(yīng)鏈決策模式研究[J];中國管理科學(xué);2006年03期

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本文編號：2439153