電腦銷(xiāo)售外文翻譯---模擬空房情況展望電子商務(wù)中的個(gè)人電腦銷(xiāo)售-電子商務(wù)-資料下載頁(yè)
2025-01-19 03:06本頁(yè)面
【導(dǎo)讀】前部署，是非常很重要的。我們已經(jīng)成功地開(kāi)發(fā)和利用仿真模型，為IBM的個(gè)。據(jù)刷新，和不確定性的需求預(yù)測(cè)，訂單規(guī)模和消費(fèi)者心目中的產(chǎn)品功能。型，我們能夠預(yù)測(cè)動(dòng)態(tài)的可用性，發(fā)貨日期，并確定了其他改進(jìn)機(jī)會(huì)。在當(dāng)今競(jìng)爭(zhēng)激烈的市場(chǎng)，實(shí)際。在多次在客戶的網(wǎng)上購(gòu)物過(guò)程。方法已被用于評(píng)價(jià)其有效性。大部分的這種用法一直是根據(jù)不同的生產(chǎn)和銷(xiāo)售情。況調(diào)查的庫(kù)存水平和客戶服務(wù)的業(yè)績(jī)和政策，庫(kù)存，制造，補(bǔ)充和運(yùn)輸。周期和庫(kù)存管理。策，交通運(yùn)輸政策，畜水平，交貨時(shí)間和客戶服務(wù)。務(wù)進(jìn)程的政策，程序辦法，并充分估計(jì)資源的各項(xiàng)工作在一個(gè)業(yè)務(wù)流程。于四個(gè)分立事件模擬。這樣做，并向前進(jìn)行。后者可用性刷新了批處理的時(shí)間表由于拖延履行的進(jìn)。態(tài)鑒于提供的數(shù)據(jù)引起的準(zhǔn)確性船舶日期計(jì)算。分配的具體組成部分在決定采購(gòu)政策，分配部。固定時(shí)間間隔發(fā)生的事件或隨機(jī)生成事件描述的分布函數(shù)。算供應(yīng)前景和預(yù)期客戶服務(wù)的投資是前運(yùn)行企業(yè)是相當(dāng)有利的任何企業(yè)。
【正文】 mer demand, which has uncertainty. The replenishment quantity is modeled using a distribution function, typically a normal distribution with certain mean and standard deviation, which represent the uncertainty of demand forecast. In this work, we use the historic demand distribution data to arrive at the distribution function. Here, various replenishment policies can be modeled to specify the frequency and size of the replenishment. Roll Forward Event As simulation clock moves from a day to another day, the ponent that has not been consumed are carried forward to a day earlier. For example, the availability quantity for the 2nd day will be the availability quantity of 1st day, and that of 3rd day will be that of 2nd day etc. Also, the availability quantity not consumed on the 1st day stayed on the same day, assuming it is nonperishable. The roll forward event can be generated in a fixed interval, ., daily, or different roll forward events can also be modeled based on the business environment. Data Refresh Event In ideal ebusiness environment, when a customer order for a specific product is accepted, the ponents that constitute the product should immediately be reserved and not available for future orders. However, in reality the availability data are not updated in real time. One of the reasons is that several puter systems are involved in processing and fulfilling customer orders, aand their data are not updated and synchronized in real time because it is expensive to have IT architecture that ensures such data munication and synchronization. Another reason is that the order fulfillment tasks, which may include scheduling, production, distribution and accounting etc., takes some time or are typically carried out as a batch process. The batch process is executed in certain time intervals, and the availability data is updated only after the fulfillment tasks are pleted. The discrepancy between the real availability (dynamic availability) and the known availability (static availability) causes the accurate ship date calculation. In this work, the ship date is puted using both dynamic and static view of the availability, as shown in the Figure 2, and the inaccuracy of the ship date calculation is estimated. The inaccuracy of ship date calculation is an important indication of customer service level. The data refresh event can be modeled as fixed interval event or randomly generated event described by distribution functions. 6 SUMMARY Customer service is one of most important factors of success and survival of enterprises in today’s dynamic business environment. Being able to estimate availability outlook and expected customer services before investment is made to run the business is quite beneficial to any enterprises. We have developed a simulation model that estimates the ship dates, one of most important customer service factors in online sales business, and how accurate the promised ship date is. By simulating various business scenarios, analyzing eexpected ship date statistics and paring the costs of running the scenarios, we were able to make intelligent business decisions to promote higher profits and better customer services. The simulation modeling work was done using the IBM WBI Modeler (IBM Corporation).
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