兩點之間哪條路線最短 看UPS如何用大數據優化送貨路線

The number of possible routes that a UPS driver could take on any given day is enormous.

在任何一天中，UPS的司機都有許多條快遞路線可以選擇。

Strike that—the number of possible routes that a UPS driver could take on any given day defies comprehension. That’s not an exaggeration.

或者換個說法——UPS的司機在任何一天中，可以選擇的快遞路線的數目都是令人難以想象的。這絕不是誇張。

A driver for the delivery company typically makes between 120 and 175 “drops” per day. Between any two of those, there are a number of available paths to take. It is, of course, in the best interest of the driver and UPS to find the most efficient route. And that is where things get complicated.

這家快遞公司的司機一般每天要送120至175次貨。在任何兩個目的地之間，都可以選擇多條路線。顯然，司機和UPS想要找到其中最有效率的那條。不過如此一來，事情就變得複雜了。

According to UPS, the number to describe the complete set of possibilities in the scenario outlined above, as calculated using combinatorial mathematics, would have 199 digits. The number of possible options would exceed the number of nanoseconds that the Earth has existed.

UPS利用組合數學的算法得出，以上所述的情景中所有可能的線路的總數，是一個199位的數字。這一數字甚至大過了換算成納秒單位的地球年齡。

“It’s huge—unimaginably large,” said Jack Levis, the company’s senior director of process management. “This is as high as you can get in analytics.”

UPS的流程管理高級總監傑克o裏維斯表示：“這數字太大了，令人難以想象。你只能從分析學上得出一個概念。”

For UPS, it was nothing if not a daunting optimization challenge. But the motivation was powerful: a reduction of just one mile a day per driver would save the company as much as $50 million.

對UPS而言，這是一項龐大的挑戰。不過他們有強烈的動力去實現路線最優化：如果每位司機每天少開一英里，公司便能省下5,000萬美元。

The Atlanta-based company’s answer? A system called Orion, short for On-Road Integrated Optimization and Navigation, named after the hunter in Greek mythology, and a big data analytics effort if there ever was one. Orion—whose algorithm was developed in the early 2000s and piloted through 2009—uses 1,000 pages of code to analyze 200,000 possibilities for each route in real time to deliver the optimal route in about three seconds’ time.

這家位於亞特蘭大的公司是如何做的？他們研發了一個名爲Orion的系統，這是道路優化與導航集成系統（On-Road Integrated Optimization and Navigation）的縮寫，也是希臘神話中獵戶座的名字。如果說現在有什麼大數據分析學上的成就的話，那就是它了。Orion的算法誕生於21世紀初，並於2009年開始試運行。該系統的代碼長達1,000頁，可以分析每種實時路線的20萬種可能性，並能在大約3秒內找出最佳路線。

“At first, the mathematicians thought it was going to take about 15 minutes to run,” Levis said. “They were pleased.”

裏維斯表示：“起初，數學家們認爲可能需要15分鐘才能算出結果。所以他們很高興。”

UPS is working to deploy the system to all of its 55,000 North American delivery routes. By the end of 2013—after being applied to just 10,000 routes so far—Orion had already saved 1.5 million gallons of fuel and 14,000 metric tonnes of CO2 emissions. The company expects to complete the rollout by 2017.

UPS正在公司全部的5.5萬條北美快遞線路上裝配這一系統。到2013年底，Orion已經在大約1萬條線路上得到使用，這讓公司節省了150萬噸燃料，少排放了1.4萬立方公噸的二氧化碳。公司計劃在2017年徹底實現該計劃。

There are two “rather inconspicuous” industries that are being disrupted by big data, according to Svetlana Sicular: transportation—which includes a logistics company like UPS—and agriculture.

根據高德納研究公司（Gartner）的分析師斯維特拉娜o西庫勒的說法，有兩個“很不起眼的”行業正在受到大數據的衝擊，一個是運輸業，其中包括UPS這類物流公司，另一個是農業。

Sicular, a Gartner analyst, believes that disruption is happening on a broad scale. Consider the commercial shipping industry: the Australian Maritime Safety Authority provides information about port activity in real time so that ships can vary their speed to save fuel and minimize port fees, Sicular said. The authority also uses geofencing—dynamic, location-based digital zones—to trigger and automate those fees, “and this is all transparent through open data,” she said.

西庫勒相信這一衝擊會波及很大範圍。西庫勒表示，可以看看通商航運業的例子：澳大利亞海事安全局（Australian Maritime Safety Authority）提供了實時的港口活動信息，船隻可以據此改變航速，節省燃料，讓港口服務費降到最低。海事局還使用了地理圍欄（一種動態的數字定位區域）來觸發和自動計算這些費用。她說：“通過公開數據，這一切都是透明的。”

It’s not just big data technologies that are causing this transformation, Sicular said. The convergence of mobile devices and cloud computing also play a major role.

西庫勒表示，導致這種轉變的不僅僅是大數據技術，移動設備和雲計算在其中也扮演了重要角色。

“Mobility is important in collecting information and providing live connection to the drivers,” she explained. “Mobility is not just about mobile devices but also about sensors in trucks, planes and ships.”

她解釋說：“在收集信息、給司機實時提供數據上，移動性起到了重要作用。這不僅是指移動設備，還包括卡車、飛機和輪船上的感應器。”

Feeling pressure to make its operations more efficient, UPS introduced handheld devices for its drivers in the 1990s. “We had to create smartphones and communications online before they existed,” Levis said. In 2008, the company installed GPS tracking equipment on its delivery trucks. Orion is layered on top of this foundation.

在提高運營效率的壓力下，UPS在20世紀90年代爲司機引入了手持設備。裏維斯表示：“我們必須在智能手機和網絡通信出現前就發明它們。”2008年，公司在運貨卡車上安裝了GPS追蹤系統，而Orion則建立在這一基礎上。

Though there’s no easy replacement for a continent-spanning fleet of vehicles—until Amazon’s delivery drones materialize, anyway—the rise of cloud computing has made it easier for startup companies to access the sophisticated technology that only the largest enterprises previously enjoyed. It behooves UPS to stay ahead.

儘管想要取代在大陸上川流不息的汽車快遞不是件容易的事——總之，在亞馬遜（Amazon）的無人機快遞正式得到使用前是這樣——但云計算的興起讓初創公司更容易接觸到之前只有大型企業才能擁有的尖端技術。UPS理應走在前面。

“To me, that’s the future of analytics and big data—not just telling you what has happened, but telling you what should happen and how to correct it in real time,” Levis said. “If a system is so smart that it predicts you’ll have a problem and solves it before it happens, it’s like Sherlock Holmes. It looks clairvoyant, but it’s not.

裏維斯表示：“對我來說，這就是分析技術和大數據的未來——不僅僅是告訴你發生了什麼，還能告訴你將要發生什麼，如何實時糾正它們。如果有個系統可以智能到預測你的問題，並在它發生前予以解決，那它就像福爾摩斯一樣了。看起來像千里眼，但實際上不是。”

“It will take a while. But that’s the vision.”

“把它變成現實還需要一段時間。不過這就是未來的景象。”