【摘要】：隨著互聯(lián)網(wǎng)滲透生活,人們消費(fèi)水平的提高和需求的不斷變化,各類產(chǎn)品的市場生命周期不斷縮短,使廢舊產(chǎn)品數(shù)量也在不斷增加,而人們環(huán)保意識的逐漸增強(qiáng),企業(yè)受到經(jīng)濟(jì)利益的驅(qū)動,發(fā)展并優(yōu)化供應(yīng)鏈逐漸變成企業(yè)建立競爭優(yōu)勢的有效手段。閉環(huán)供應(yīng)鏈管理最重要的一個(gè)職能是協(xié)調(diào)定價(jià),它與產(chǎn)品的回收、需求和系統(tǒng)運(yùn)作效率有一定的關(guān)系。然而傳統(tǒng)的博弈理論只能系統(tǒng)地分析其供應(yīng)鏈某個(gè)因素的變化對其利潤的影響,而不能幫企業(yè)做出定價(jià)的最終決策,所以我們使用遺傳算法,對供應(yīng)鏈模型進(jìn)行仿真分析。遺傳算法是一種根據(jù)生物界自然選擇和自然遺傳機(jī)制的隨機(jī)搜索算法。它特別適用解決使用傳統(tǒng)搜索方法難以處理的復(fù)雜問題和非線性問題,可廣泛用于機(jī)器學(xué)習(xí)、組合優(yōu)化、人工智能等領(lǐng)域,是21世紀(jì)智能計(jì)算中的關(guān)鍵技術(shù)之一。鑒于此,本文在總結(jié)相關(guān)文獻(xiàn)研究的基礎(chǔ)之上,對B2C環(huán)境下閉環(huán)供應(yīng)鏈定價(jià)決策建立模型,并使用遺傳算法進(jìn)行優(yōu)化決策。其主要研究內(nèi)容如下:(1)對閉環(huán)供應(yīng)鏈產(chǎn)品定價(jià)問題進(jìn)行建模,建立了同一市場的不同決策主體下的決策模型:分散化決策模型、集中化決策模型和基于分散化決策下的契約協(xié)調(diào)成本分擔(dān)契約決策模型;(2)提出了基于多目標(biāo)遺傳算法的閉環(huán)供應(yīng)鏈產(chǎn)品定價(jià)求解方案,應(yīng)用多目標(biāo)遺傳算法對閉環(huán)供應(yīng)鏈產(chǎn)品進(jìn)行優(yōu)化定價(jià);(3)對決策模型及優(yōu)化定價(jià)方案進(jìn)行仿真分析,快捷準(zhǔn)確地知道如何確定銷售價(jià)格和回收價(jià)格可以使制造商和零售商利潤達(dá)到最大,為以后企業(yè)的定價(jià)管理決策提供了很大的幫助。本文的研究結(jié)果表明,遺傳算法對企業(yè)的定價(jià)決策有很直觀的輔助作用;B2C環(huán)境下的閉環(huán)供應(yīng)鏈項(xiàng)目選擇合理契約協(xié)調(diào)機(jī)制可以使得閉環(huán)供應(yīng)鏈系統(tǒng)獲得最佳的經(jīng)濟(jì)收益。
[Abstract]:With the penetration of the Internet into life, the improvement of people's consumption level and the constant change of demand, the market life cycle of all kinds of products is continuously shortened, the quantity of waste products is also increasing, and people's awareness of environmental protection is gradually strengthened. Driven by economic benefits, the development and optimization of supply chain has gradually become an effective means for enterprises to establish competitive advantage. One of the most important functions of closed-loop supply chain management is to coordinate pricing, which has a certain relationship with product recovery, demand and system operation efficiency. However, the traditional game theory can only systematically analyze the influence of a certain factor in its supply chain on its profit, but can not help the enterprise to make the final decision of pricing. So we use genetic algorithm to simulate the supply chain model. Genetic algorithm is a random search algorithm based on natural selection and natural genetic mechanism. It is especially suitable for solving complex and nonlinear problems which are difficult to deal with by using traditional search methods. It can be widely used in the fields of machine learning, combinatorial optimization, artificial intelligence and so on. It is one of the key technologies in intelligent computing in the 21st century. In view of this, on the basis of summarizing the relevant literatures, this paper establishes the model of the closed-loop supply chain pricing decision in B2C environment, and uses genetic algorithm to optimize the decision. The main research contents are as follows: (1) the pricing problem of closed-loop supply chain products is modeled, and the decision model of different decision makers in the same market is established: decentralized decision model. Centralized decision model and contract coordination cost sharing contract decision model based on decentralized decision; (2) A solution of closed-loop supply chain product pricing based on multi-objective genetic algorithm is proposed, and the multi-objective genetic algorithm is applied to optimize the pricing of closed-loop supply chain products. (3) the decision model and the optimized pricing scheme are simulated and analyzed, and how to determine the sales price and the recovery price quickly and accurately can make the manufacturer and retailer profit maximum. It provides a great help for the decision of pricing management in the future. The results of this paper show that the genetic algorithm can directly assist the enterprise pricing decision, and the reasonable contract coordination mechanism of the closed-loop supply chain project selection under B2C environment can make the closed-loop supply chain system obtain the best economic benefits.
【學(xué)位授予單位】：湖南科技大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：F274

【參考文獻(xiàn)】

相關(guān)期刊論文 前10條

1 李輝;汪傳旭;歐衛(wèi);;閉環(huán)供應(yīng)鏈企業(yè)合作減排與定價(jià)策略[J];商業(yè)研究;2017年05期

2 石丹;魏超;戴明宏;;閉環(huán)供應(yīng)鏈回收企業(yè)兩種融資模式下決策分析[J];北京郵電大學(xué)學(xué)報(bào)(社會科學(xué)版);2017年02期

3 高攀;丁雪峰;代美玲;;考慮二手產(chǎn)品專利保護(hù)的閉環(huán)供應(yīng)鏈翻新策略與協(xié)調(diào)機(jī)制[J];物流技術(shù);2017年04期

4 劉光富;劉文俠;;雙渠道再制造閉環(huán)供應(yīng)鏈差異定價(jià)策略[J];管理學(xué)報(bào);2017年04期

5 祖峰;劉力鋼;李昕;;關(guān)于雙渠道供應(yīng)鏈最優(yōu)定價(jià)策略研究[J];價(jià)格理論與實(shí)踐;2017年01期

6 孫浩;葉俊;胡勁松;達(dá)慶利;王凱;;不同決策模式下制造商與再制造商的博弈策略研究[J];中國管理科學(xué);2017年01期

7 葉俊;孫浩;;不同回收成本結(jié)構(gòu)下考慮參考價(jià)格的閉環(huán)供應(yīng)鏈定價(jià)策略[J];物流科技;2017年01期

8 祝凌燕;;電子商務(wù)環(huán)境下閉環(huán)供應(yīng)鏈定價(jià)策略探討[J];商業(yè)經(jīng)濟(jì)研究;2016年22期

9 周溢洋;;雙渠道閉環(huán)供應(yīng)鏈差異定價(jià)協(xié)調(diào)機(jī)制[J];物流工程與管理;2015年11期

10 韓秀平;陳東彥;陳德慧;侯玲;;再制造率隨機(jī)的閉環(huán)供應(yīng)鏈產(chǎn)品差別定價(jià)策略[J];控制與決策;2015年11期

相關(guān)碩士學(xué)位論文 前7條

1 王羽;不同政府激勵機(jī)制下閉環(huán)供應(yīng)鏈定價(jià)策略研究[D];重慶交通大學(xué);2016年

2 趙琳;互惠利他偏好下的閉環(huán)供應(yīng)鏈定價(jià)策略研究[D];中北大學(xué);2016年

3 原泉;閉環(huán)供應(yīng)鏈的差異定價(jià)策略及協(xié)調(diào)研究[D];天津大學(xué);2014年

4 王煜;電子市場與傳統(tǒng)市場中供應(yīng)鏈協(xié)調(diào)機(jī)制的研究[D];北京郵電大學(xué);2012年

5 江偉;混合回收閉環(huán)供應(yīng)鏈差異定價(jià)策略研究[D];浙江工業(yè)大學(xué);2011年

6 歐陽建軍;基于遺傳算法的閉環(huán)供應(yīng)鏈中若干問題研究[D];湖南大學(xué);2008年

7 宿紹鑫;閉環(huán)供應(yīng)鏈中制造商對廢舊品分級定價(jià)回收的策略研究[D];上海交通大學(xué);2007年

，

本文編號：2399853