供應鏈管理paper代寫范文：Simulation in Logistics and Supply Chain
供應鏈管理paper代寫范文-物流與供應鏈仿真。本文是一篇由本站提供的留學生供應鏈管理專業paper代寫范文。本篇paper的主要任務是免除物流和供應鏈中模擬與計劃和控制的關系。為了了解模擬是如何用于分析供應鏈績效的，Paper對文獻綜述進行了批判性分析。本篇paper研究的主要重點是分析在供應鏈規劃和控制方面模擬中使用的各種方法，以分析各種方法的利弊。以下內容就是本篇供應鏈管理paper代寫范文，供參考。
Introduction:引言
The main task of this paper is to exemine how simulation is being used in logistics and supply chain (LSC) in relation to planing and control. In order to understand how simulation is being used to analyse the supply chain performance, a literature review was critically analyse. The main focus of this reserch was to analyse the various methods being used in simulation as regard the supply chain planing and control in order to analyse the benefit and contrain of the various method ( ).
A sample of problem in SC was identify and treated with one of the methods of simulation in order to measure the efficiency and effectivenes within SC. Conclusion was drawn which compares and contras both approch to measure the weakness and streagnth in diffrent circumstancies.
本篇paper以供應鏈中的一個問題樣本為例，用模擬方法之一對其進行識別和處理，以衡量供應鏈的效率和有效性。
Problem Identification and Description 問題識別和描述
Litrature Review 文獻綜述
A review recently by Cid Yanez et al., (2009) Identified more comprehensive taxonomy of the different types of simulation wich ara: continuous, discrete, System Dynamics, Gaming, Agent, Artificial Intelligence, Virtual Reality etc. However, thier are quite of number of methods or techniqures used in planing accross supply chain, namely XML, Spreadsheet, Mathematical Modelling, Java, potal Software, Matlab, etc. In contrast Skiadas and Skiadas, (2009) argue that methods or techniqures like Spreadsheet, XML, Java and Genetic Algorithm were not actual simulation techniqure but rather are merely simple analysis tools and programming methods wich is categorised under Discrete Mathematical Model wich are static in nature. In the same vein Small et al., (2013) suggests that Discrete mathematical model is diffrent in nature because it try to find an optimal solution to a problem in the present rather than in the future. In view of DAVIS, EISENHARDT and BINGHAM, (2007) agrees that mathematical modelling techniqures cannot deal with dynamic and complex situiation expecially in gaining competative advantage through the supply chain network. This means that mathematical model or techniques is not considered as the best in dealing with real phenomenon. Example product demand forecasting. Conversely, Dynamic simulation modelling is regarded as poor modelling techniqures as it lacks the ability to handle too detailed LSC micro problems such as job sequencing (Longo, 2011). However as ponted out by Chopra and Mendl (2007) there are three basic supply chain simulation in planinig and control wich are: System Dynamics (SD), Discrete Event Simulation (DES), and Agent Based Modelling (ABM). Accordingly, Lorenz and Jost (2006) have identified these three basic types of simulation in supply chain planing and optimization, each problem has a particular approach being used to find optimal solution. In view of the defination provided by copra and mendl (2011) in relation to supply chain management decision making, identified two main problem namely; strategic and opertational wich can be tackled by these approch (i.e. SD, DES ABM). ( ) suggest that In order to make the right decision it is important to prepare them with appropriate planning and control.
Cid Yanez等人最近的一篇綜述對不同類型的模擬進行了更全面的分類：連續、離散、系統動力學、游戲、代理、人工智能、虛擬現實等。然而，在跨供應鏈規劃中使用了相當多的方法或技術，即XML、電子表格、數學建模、Java，potal Software、Matlab等。相比之下，Skiadas和Skiadass認為，電子表格、XML、Java和遺傳算法等方法或技術不是實際的模擬技術，而只是簡單的分析工具和編程方法，屬于本質上靜態的離散數學模型。同樣，Small等人認為，離散數學模型本質上是不同的，因為它試圖在當前而不是未來找到問題的最優解。鑒于DAVIS，EISENHARDT和BINGHAM，一致認為，數學建模技術無法處理動態和復雜的情況，尤其是在通過供應鏈網絡獲得競爭優勢方面。這意味著數學模型或技術在處理真實現象時并不被認為是最好的。產品需求預測示例。相反，動態模擬建模被認為是較差的建模技術，因為它缺乏處理過于詳細的LSC微觀問題（如工作順序）的能力。然而，正如Chopra和Mendl提出的那樣，在規劃和控制中有三種基本的供應鏈模擬：系統動力學（SD）、離散事件模擬（DES）和基于代理的建模。因此，Lorenz和Jost已經確定了供應鏈規劃和優化中的這三種基本模擬類型，每個問題都有一種特定的方法來尋找最優解。鑒于copra和mendl對供應鏈管理決策的定義，確定了兩個主要問題：；這些方法（即SD、DES ABM）可以解決戰略和操作問題。建議為了做出正確的決定，重要的是要為他們做好適當的規劃和控制。
Similarly, Arne Schuldt (2010) state that the primary supply chain function are applied in order to tackle challenges usually, each of the function is not sufficient alone to tackle the challenges instead multiple functions contributed by multiple techniques or model must be combine to supply network in order to make the right decision. For instance, Baril et al. (2016) use both approch to improve health care service delivery by reducing patient delay using DES, SD to improve patient pathways and ABM for quick implementation process. As can be seen both method can be used to achieve SC strategic and planning objectives
同樣，paper引用Arne Schuldt的理論指出，應用主要供應鏈功能是為了應對挑戰，通常，每個功能都不足以單獨應對挑戰，相反，必須將多種技術或模型貢獻的多個功能組合到供應網絡中，才能做出正確的決策。例如，Baril等人使用DES、SD改善患者路徑和ABM快速實施過程，通過減少患者延遲來改善醫療服務提供。可以看出，這兩種方法都可以用于實現供應鏈戰略和規劃目標
However, Lean thinking simulation and implementation has emerged in various segment of the suppy chain particularly in manufacturing and recently in the healthcare because, recent litrature has shown significant benefit such as increased patient and management throughput( ). In view of ( ) every oranisation has similar process of simulation implemetation wich must start with define value, measure, analyse, improve and control as indicated in the following figure 1
然而，精益思維的模擬和實施已經出現在供應鏈的各個環節，特別是在制造業和最近的醫療保健領域，因為最近的文獻顯示了顯著的好處，如增加了患者和管理吞吐量。每一個創造有類似的模擬實施過程，必須從定義值、測量、分析、改進和控制開始，如下圖1所示
Figure 1 Organisational Approch of Simulation
Source: (Baril et al. 2015)
STRENGTHS AND WEAKNESSES OF THE THREE (3) APPROACHES 三種方法的優缺點
System Dynamics 系統動力學
Despite the potential benefit and broad range of applications of SD in supply chain domains, the SD techniques is often regarded as a means suited to handle only macro SC problems and relational policy problems before implemetation ( ). Conversely, SD is regarded as a poor modelling technique but, as agued by ( ) that System Dynamics need to be complemented by micro modelling techniques in many situation, such as credible models which lies in the body domain of Descret event simulation that is strong and beneficial for analysing detailed and complex situaions. However, from its earliest to the recent reserch in SC ( ) has identified that feedback flow of information has been a core central features of SD and the techniques has been used to analyse many SC problems where studies finding suggested that SD is a continuous and syncronose procesess where operations are aggregated together rather than being as seprate or discrete entities. For This reason it has being suggests that the the SD techniques may be less effective to tackle problems where human behaviour or individul are observed. For example shoppers habit in Tesco. In the same vein, ( ) that one of the constraint of SD, is not effective to tracking movement of individual in space and location. In other word, one of the major aim of SC is targeted at individaul customer but, SD being a cyclical process may not model the movement of individual as it tend to varies from one point in time to another. For instance, the Impact of Brexit policy in the uk to Eu may have negative impact on various supply chain networks (Viner, 2016). Therefore, SD is aims only at addressing policy problems that are strategic in nature rather than tactical or operational level particularly dealing with human interaction in SC ( ). In contrast, many scholars in the field of SC claims that ABM can model detailed distinct behaviour where spatial relationships co-exist. And ABM can be used to model the behaviour of distict supply chain or distinct suppy node ( ). For example SD deals with problems like:
盡管SD在供應鏈領域具有潛在的好處和廣泛的應用范圍，但SD技術通常被認為是一種在實施前僅適用于處理宏觀供應鏈問題和關系政策問題的方法。相反，SD被認為是一種較差的建模技術，但正如所困擾的那樣，在許多情況下，系統動力學需要由微觀建模技術來補充，例如位于Descret事件模擬主體領域的可信模型，該模型對于分析詳細和復雜的情況是強大和有益的。然而，從最早到最近的SC研究已經確定，信息的反饋流一直是SD的核心核心特征，并且該技術已被用于分析許多SC問題，其中研究發現，SD是一個連續和同步的過程，其中操作被聚合在一起，而不是單獨或離散的實體。因此，有人認為，SD技術在解決觀察到人類行為或個體的問題方面可能不太有效。例如，特易購的購物者習慣。同樣，SD的約束之一對于跟蹤個體在空間和位置上的運動是無效的。換句話說，SC的主要目標之一是針對個人客戶，但SD作為一個周期性過程，可能不會對個人的運動進行建模，因為它往往在不同的時間點有所不同。例如，英國脫歐政策對歐盟的影響可能會對各種供應鏈網絡產生負面影響。因此，SD僅旨在解決戰略性的政策問題，而不是戰術或操作層面的問題，特別是處理SC中的人際互動。相比之下，SC領域的許多學者聲稱，ABM可以在空間關系共存的情況下對詳細的不同行為進行建模。ABM可用于離散供應鏈或離散供應節點的行為建模。例如，SD處理以下問題：
Supply chain redesign 供應鏈重新設計
Quality perception and Quality Control 質量感知與質量控制
E-collaboration 電子協作
Impact of demand amplification on transport cost 需求放大對運輸成本的影響
Cycle time compression and Performance metrics 循環時間壓縮和性能指標
The effect of batching on bullwhip 配料對牛鞭的影響
Discrete Event Simulation (DES) 離散事件仿真
Base on litrature reviews, claims that DES is very effective to handle the problem of variation in time intervals ( ) In similar vein, DES in supply chain planing and control can be used to measure relationships between entities in it strategic form. For example……………………………. ( ) argue that DES is not very effective for modelling policy in it generic level. Of course in reality SC problems under critical study ranging from planing, operations, and strategy, a more embodied discription by many leading scholar in the field of SC emphasised the need of of DES in the operational and planing level whereby the DS is more practicable in application to strategic level problems ( )
基于文獻綜述，聲稱DES在處理時間間隔變化問題方面非常有效。類似地，供應鏈規劃和控制中的DES可以用于以戰略形式衡量實體之間的關系。認為DES在其通用級別上對政策建模不是很有效。當然，在現實中，從規劃、作戰和戰略等關鍵研究中的SC問題，許多SC領域的領軍學者更具體地描述了DES在作戰和規劃層面的必要性，從而使DS在應用于戰略層面的問題時更具實踐性
Agent base Simulation 基于Agent的仿真
Agent Based Modelling ABM is an emerging method of simulation capable of application throughout the range from the strategic to operational level in the supply chain Arvitrida, Robinson and Tako, (2015) . As an emerging model, a number of views have been made for ABM. For instance, agent base model of simulation can be use to exemine distinct behaviour where spatial interconnection of relationships core exiest ( ). Similarly, agent based simulation can be used to model the behaviour of individual characteristics and it has being term as the only techniqures that can model certain features such as “agilty” to respond to ever increasing level of volitality of deman, agility in the sense of quick response to what ever situation under study (Critopher, 2011 ). ABM deals with supply chain ploblem in the following:
基于Agent的建模ABM是一種新興的模擬方法，能夠在供應鏈的戰略到運營層面應用。作為一種新興的模式，人們對反導提出了許多看法。例如，模擬的基于代理的模型可以用于免除關系的空間互連最核心的不同行為。類似地，基于智能體的模擬可以用于對個體特征的行為進行建模，它被稱為唯一可以對某些特征進行建模的技術，如對不斷提高的需求者意志水平做出反應的“敏捷性”，對所研究的情況做出快速反應的敏捷性。ABM在以下方面處理供應鏈問題：
Market dynamics 市場動態
Modelling control elements 建模控制元素
Human behaviour on bullwhip effect 牛鞭效應下的人類行為
Human behaviour and trust 人類行為和信任
Collective customer collaboration 集體客戶協作
Table 1 Agent Base Simulation Source: 表1基于Agent的模擬來源：
Discussion and Conclusion 討論和結論
The review of the litrature in this paper point out the benefit and constraint. In other words, it differenciate the various method of simulation in sc perspective. It shows that the various method varies and differs in scope both in customs and in practice or reality. In particular, SD is predominantly regarded as static in nature as it involves in continuous process or vertual techniques to tackle macro supply chain problems that are strategic in nauture. On the other hand, both DES and ABM are complementry to model entities in the same supply chain to varioius supply networks.
本篇paper對文獻進行了綜述，指出了其優點和制約因素。也就是說，它從供應鏈的角度區分了各種模擬方法。它表明，無論是在習俗上，還是在實踐或現實中，各種方法的范圍都是不同的。特別是，SD在本質上主要被視為靜態的，因為它涉及到解決宏觀供應鏈問題的連續過程或實際技術，而這些問題在航行中具有戰略意義。另一方面，DES和ABM都是對不同供應網絡的同一供應鏈中的實體建模的補充。
However, the major challengies to be fully and critcally analyse by researchers remains on the ability to match DS and ABM to work together in order to tackle companies problem internally and externally.
然而，研究人員需要全面而標準地分析的主要挑戰仍然是能否將DS和ABM相匹配，以便在內部和外部解決公司問題。
Thus, most supply network constrain related to timing is that, the time intended to find optimal solution mostly exceed the parameter of the time considered for executing the the SC respective function. This is more so for the fact that, static planning cannot be applied externally (I.e. outside the organisation) but rather internally, within the organisational boundaries of control as it involves continues or virtual process. Furthermore, the nature of ABM, in decision-making cannot be achieve using centralised approach because, not all information are centrally available.
因此，與時序相關的大多數供應網絡約束是，旨在找到最優解的時間大多超過執行SC各自函數所考慮的時間參數。更重要的是，靜態規劃不能在外部（即組織外部）應用，而是在內部，在組織控制范圍內應用，因為它涉及持續或虛擬過程。此外，ABM的性質，在決策中不能使用集中的方法來實現，因為并非所有信息都是集中可用的。
Finally, it may be possible in the future to identify maximal self-contained system within lager systems that can be centrally control at the same time re-planning in the continuous process. But most likely that system of computational complexity is likely to exists within the boundaries of one company.
最后，paper總結到，在未來可能會在更大的系統中識別出最大的自包含系統，這些系統可以在連續過程中進行重新規劃的同時進行集中控制。但最有可能的是，這種計算復雜性的系統很可能存在于一家公司的邊界內。本站提供各國各專業paper范文，paper代寫以及paper寫作輔導，如有需要可咨詢本平臺。
