200907833 九、發明說明： 【發明所屬之技術領域】 本發明係關於一種商務物流途徑建立方法，特別是 關於結合資料分群演异法及節省法，用以解決車輛途程問 題（VPR)之商務物流途徑建立方法。 【先前技術】 一 切又仃马5故如何選用適 當之運送綠崎錢輸縣，係城少物㈣成本的重 要課通之一。一般而言，物流行為之車輛途程問題（VPR )係於預定容量的條件下，所有車輛自—物流中 亚依循特定路線經過數個物流需求點，各物流需求點^必 須被服務一次，且不能重覆 ，白'、 ]到該物流中心。因此，前述各求點’最後再回 其輯、時間及:本=劃： 更馮几善之車輛服務的行車路線。 習知行車路線薄查彳 號「行車路線規劃系I華民國公告第歸]9 裝有電子導航程式之带/」χ明專利5其係應用於安 理令心，用以收集法包含：建立資料處 令該電子裝置執行H =亚將其鮮至資料庫令； 由該電子裝置取得該式以規劃行車路線；以及藉 路況資訊，並比對所::处理:心之資料庫所儲存之即時 線重疊的情形，以作仔之即^'路況資訊與規劃之行車路 前述習知行車路線車路線之依據。然而， ΡΚ10411 07/08/14 — '僅铩稭由收集路況資訊，作為 200907833 行車路線規劃之參考依據，其並未針對各車輛分別服務數 個物流需求點時，如何有效規劃效率較佳之行車路徑，以 及更有效降低行車時間成本等問題進行考量。 又’爹考國㈣先前已揭示之各種相敎獻，其亦 有學者試㈣用如模賴纽（Simulated sa )、禁忌搜尋法（Tabu Search，TS)' _群聚演算法（200907833 IX. Description of the invention: [Technical field to which the invention pertains] The present invention relates to a method for establishing a business logistics route, in particular to a business logistics approach for solving a vehicle transit problem (VPR) by combining data grouping and different methods and saving methods. Establish a method. [Prior Art] All of them have to choose the appropriate transportation of the green food to the county, which is one of the important lessons for the cost of the city. Generally speaking, the vehicle behavior problem (VPR) of logistics behavior is under the condition of predetermined capacity. All vehicles from the logistics-Central Asia follow a specific route through several logistics demand points, and each logistics demand point must be serviced once and cannot Repeat, white ', ] to the logistics center. Therefore, the above-mentioned various points of demand are finally returned to the series, time and time: Ben = plan: The driving route of the vehicle service of Feng Fengshan. The Customs Driving Routes, the thin track 彳 「 行 行 行 行 行 华 华 华 装有 装有 装有 装有 装有 装有 装有 装有 装有 装有 装有 装有 装有 装有 装有 装有 装有 装有 装有 装有 装有 装有 装有 装有 装有 装有 装有 装有 装有 装有 装有 装有 装有 装有 装有 装有 装有 装有Ordering the electronic device to execute H = Asia to its database order; obtaining the form by the electronic device to plan the driving route; and borrowing the road information and comparing the information:: Processing: the instant stored in the database of the heart The situation in which the lines overlap is used as the basis for the traffic information of the above-mentioned conventional driving route. However, ΡΚ10411 07/08/14 — 'Only the stalks are collected by the road conditions as a reference for the 200907833 driving route planning. How to effectively plan the better driving route when the vehicle does not serve several logistics demand points respectively? And more effective considerations such as reducing the cost of travel time. In addition, the various examinations that have been previously revealed by the country (4) have also been tested by scholars (4) using Simulated sa and Tabu Search (TS) ' _ group aggregation algorithm (
Am Colony 〇ρ— ’ AC〇)或料法等方法，用以 解決車輛途程問題（VPR)，以便規劃出一行車路線。然 =j各種方法亦未能相互搭配’以有效提升規劃後之 :車路線品質；或者是配合使用資料分群方法，以事先簡 進一步降低其行車路線_之時这各種方法仍無法 纽德作古“間成本’且所規劃出之行 ' 班完善之處。基於上述原因，有必要進一牛 良上述各則知行車路線規射法。 乂 J有鑑於此’本發明改良上述各習知行車路 流需长點人斗分群演算法將鄰近之數個物 而衣點合併~屬為同一群 用即名法快速排定簡化後之利 後則進一步還 广L而求點的灯車路線；最 有較低配送成本之行車路線。 、·良措以獲件具 【發明内容】 x月之主要目的係提供—種商矛务物浐逹;^逮办 貝科刀群凉异法事先簡化欲排定之行車路線 PK10411 07/08/14 200907833 親始行車路線，最後還原及局部 規刀始行車路線，以便完成最終行車路線之排定作業 斗使:本發明具有可大幅降低行車路線規劃時間成本及提 升行車路線規劃品質之功效。 之人要目的係提供—種商務物流途徑建立方 法〜、係更進-步藉由i蟻群聚演算法（Ant colony =mlzati°n，A⑼賴丨㈣之行車路線，並配合使 用hpt法」來改善該碼蟻群聚演算法所建構之行車路 線，使得本發明具有可降低行車成本，以及更進一步提升 行車路線規劃品質之功效。 、根據本發明之紐物流途輯立方法，其包含一物 ，需求點合併步驟’係藉由資料分群演算法將鄰近距離之 欠個物流需求點合併歸屬為同一群組，再依據各群組設定 3)數個合併需求點，用以簡化欲排定之行車路線卜初始路 徑建立步驟，係利用節省法分別計算各合併需求點之節省 值，以建立一初始行車路線；一物流需求點還原步驟，係 將各合併需求點還原為原先之物流需求點座標及數量，並 依，該初始行車路線規劃各物流需求點之行車路線，以完 成最終行車路線之規劃作業。 凡 【實施方式】 為讓本發明之上述及其他目的'特徵及優點能更明 顯易懂’下文特舉本發明之較佳實施例，並配合所附圖 ’作样細說明如下： 请參照1及2圖所示，本發明較佳係藉由—電腦系 ΡΚ10411 07/08/14 200907833 統（未繪不）執行如下所述之相關步驟，以提升行車路線 ^規劃效率。該電腦系統係連接一資料庫（未繪示），該 資料庫則用以儲存至少一物流中心η及數個物流需求點 12之座標位置，並將該物流中心11及各物流需求點12 。又定為一貧料集（dataset)，以便執行後續之行車路線規 劃作業。本發明第一實施例之商務物流途徑建立方法，其 已3物々’L茜求點合併步驟S11、一初始路經建立步驟 S12及一物流需求點還原步驟S13。藉此，以尋求具有較 佳效率之行車路線。 "、又 “、凊參照第1至3圖所示，本發明第一實施例之物流 需求點合併步驟S11，其係藉由資料分群演算法將鄰近距 離之各物流需求點12合併歸屬為同—群組2，再依據各 群組2設定如第3圖所示之數個合併需求點3，以事先簡 】化欲排疋之行車路線。更詳言之’如圖所示之較佳實施例 -中’本發明係採用「㈣CAN分群演算法」進行各物流 ，求點12之資料分群作業。一般而言，順⑽分群演 算法係包含-半徑u)參數及一最少包含點（Mmpts) 等二種參數。該半徑U)參數之概念係認定在某個距離 2之物肌而求點12皆視為鄰居，而可以合併成為—合併 需求點3，例如：以一物流需求點12為中心，其半徑一 公里内之各物流需求點12可設定為—合併需求點^以 利進行後續行車路線規劃作業；又，該最少包含點（ MinPts)參數之概念係認定前述預定半獲距離内至少要大 於某個數量之物流需求點12，方可合併成為一合併需求 PK10411 07/08/14 8 — 200907833 點3，例如：該預定半徑距離内至少要包含二個或 上之物流需求點12，方可設定為一合併 藉此’使用者可依自身之行車路線_需求，分別 設定厨述半徑⑴參數及最少包含點（Mmpts)參數， 其中較佳係為距離該物流中心u較遠之物流需求點^ 該半徑⑷參數相對設定較大；距離該物流中心，· ^ f之物流需求點12 ’該半徑…參數相對設定較小； 則述半徑U)參數之該設定方式的優點在於··距離該物 流中心u較遠之物流需求點12，所屬路線通常為同—路 線；距離該物流中心；11較近之物流需求點12，由於彼此 相對距雜近，故可能屬於兩條不同之路線。因此， j種參數輸入該電腦系統時，即可藉由該電腦系統將^ 前述二個參數之規則的物流需求點12合併歸屬為同一群 組2 ’再依據各群組2設定數個合併需求點3，用以事先 簡化欲排定之行車路線。 jj請參照第1及4圖所示，本發明第一實施例之初始 路徑建立步驟S12，'其較佳係藉由如下所述之正規化公式 (由 Morgan〔 Morgan and Mumf〇rd，2〇〇5〕提出），用以 事先改變各合併需求點3之座標，使得座標更新後之各合 併需求點3,的分佈較為平均，以利於後續利用「節省法 (Clarke and Wright，1964)」規劃出更佳品質之行車路線 。該用以改變各合併需求點3座標之正·公式係為： x’= (int)〇 + (r 一 05)) * / * 尤） 〆=(int)(少 + (r 一 0.5)) * y * r) 其中，"為―符合均等分配（Uniform Distributi⑽）， PK10411 07/08/14 —9 — 200907833 其係介於0至1之間所隨機產生的—她值，· 子（Pertu—麵Factor)，其係改變座標 夫，因 較佳範圍係界定於〇·〇1至〇.2之間；χ為丨χ，數5且Am Colony 〇ρ— ‘AC〇) or method of materialization to solve the Vehicle Routing Problem (VPR) in order to plan a route. However, the various methods have not been able to match each other' to effectively improve the planning: the quality of the vehicle route; or the use of the data grouping method to further reduce the driving route in advance _ when these methods are still unable to make New The cost of 'and the planned trip' is perfect. For the above reasons, it is necessary to enter the above-mentioned various lanes of the vehicle route. 乂J In view of this, the present invention improves the above-mentioned various conventional road traffic. It is necessary to use a long-term human-group algorithm to merge several nearby objects and clothing points. It belongs to the same group, using the instant name method to quickly simplify the simplification, and then further widen the L-light route. Driving route with lower distribution cost. ···························································································· Set the driving route PK10411 07/08/14 200907833 Start the driving route, and finally restore and partially start the driving route to complete the final driving route. The invention has the ability to greatly reduce the planning of the driving route. The cost and the effect of improving the quality of the driving route planning. The purpose of the person is to provide a method for establishing a business logistics path~, and the system is further advanced by the i colony algorithm (Ant colony = mlzati°n, A (9) Lai Wei (4) The driving route and the hpt method are used to improve the driving route constructed by the code ant colony gathering algorithm, so that the invention has the effect of reducing the driving cost and further improving the planning quality of the driving route. New logistics method, which includes a thing, the demand point merge step 'by the data grouping algorithm to merge the adjacent logistics demand points of the adjacent distance into the same group, and then set 3) according to each group The combination of demand points is used to simplify the initial route establishment step of the route to be scheduled, and the savings value of each combined demand point is separately calculated by the saving method to establish an initial driving route; The consolidated demand point is restored to the original logistics demand point coordinates and quantity, and according to the initial driving route, the driving route of each logistics demand point is planned. Complete the final route of the planned work. The above and other objects and features of the present invention will become more apparent and understood. As shown in FIG. 2, the present invention preferably performs the following related steps by the computer system 10411 07/08/14 200907833 (not shown) to improve the driving route planning efficiency. The computer system is connected to a database (not shown) for storing at least one logistics center η and a number of logistics demand points 12, and the logistics center 11 and each logistics demand point 12 . Also defined as a dataset to perform subsequent driving route planning operations. The business logistics route establishing method of the first embodiment of the present invention has a step S11, an initial path establishing step S12, and a logistics demand point restoring step S13. In this way, seek a route with better efficiency. ", and, as shown in Figures 1 to 3, the logistics demand point combining step S11 of the first embodiment of the present invention combines the logistics demand points 12 of the adjacent distances by the data grouping algorithm as Same as - group 2, and then according to each group 2, set several merge demand points 3 as shown in Fig. 3, in order to simplify the driving route to be exhausted in advance. More specifically, as shown in the figure The preferred embodiment - the present invention uses the "(four) CAN grouping algorithm" for each logistics, and the data grouping operation of point 12 is sought. In general, the cis (10) grouping algorithm includes two parameters: a radius u) parameter and a minimum inclusion point (Mmpts). The concept of the radius U) parameter is that the object muscle at a certain distance 2 is regarded as a neighbor, and can be merged into a merge demand point 3, for example, centered on a logistics demand point 12, and its radius is one. Each logistics demand point 12 within a kilometer may be set to - merge the demand point ^ to facilitate subsequent route planning operations; and the concept of the minimum inclusion point (MinPts) parameter determines that the predetermined half-acquisition distance is at least greater than a certain The quantity of logistics demand point 12 can be merged into a combined demand PK10411 07/08/14 8 — 200907833 point 3, for example: the predetermined radius distance must contain at least two or above logistics demand points 12, in order to be set to By combining, the user can set the cooking radius (1) parameter and the minimum inclusion point (Mmpts) parameter according to their own driving route _ demand, wherein the preferred one is the logistics demand point far from the logistics center u. The radius (4) parameter is relatively large; from the logistics center, · ^ f logistics demand point 12 'the radius... parameter relative setting is small; then the radius U) parameter has the advantage of this setting method is · Logistics demand point 12 far from the logistics center u, the route is usually the same route; from the logistics center; 11 near the logistics demand point 12, due to the relative distance between each other, it may belong to two different route. Therefore, when j parameters are input into the computer system, the computer system can combine the logistics demand points 12 of the above two parameters into the same group 2' and then set several merge requirements according to each group 2. Point 3 is used to simplify the route to be scheduled in advance. Jj, as shown in Figures 1 and 4, the initial path establishing step S12 of the first embodiment of the present invention, 'it is preferably by the normalization formula as follows (by Morgan [Morgan and Mumf〇rd, 2〇] 〇5] proposed) to change the coordinates of each combined demand point 3 in advance, so that the distribution of the combined demand points 3 after the coordinates are updated is relatively average, so as to facilitate the subsequent use of the "Clarke and Wright (1964)" plan. Better quality driving routes. The positive formula for changing the coordinates of each combined demand point is: x'= (int)〇+ (r_05)) * / * especially) 〆=(int) (less + (r a 0.5)) * y * r) where " is equal to Uniform Distributi(10), PK10411 07/08/14 —9 — 200907833 It is randomly generated between 0 and 1 — her value, · Son (Pertu -Factor), which changes the coordinate number, because the preferred range is defined between 〇·〇1 to 〇.2; χ is 丨χ, the number is 5
，其係各合併需求點3中，Χ座標最大值與I 中’Υ座“取大值與γ座標最小值之間的差距。而· 請參閱第4圖所示，當藉由上述 ，併需求點3,之座標後，即可進—步藉新各 异座標更新後之各合併需求點3,的節 ，」計 選擇進行連結（Join)、併入（Attach)及合併為是否 等三種動作之依據。由於「節省法」—般具有較作:吻） 解品質，故可順利建立一初始行車路線“:始 技7於此不再寶述），並於完二習知 依，該初始行車路還原各合併需求點3之原先座標。P =所示，係為事先更新各合併需求點3之座標:再 —用^法」所建立之行車路線示意圖；又如第$圖所 ϋ ί未事先諸Ϊ合併需求點3之座標，而直接利用 即/」所求得之行車路線示意圖。因此，當比較第* ，5圖時，即可明顯看出第4圖之行車路線品質（距離成 =顯優於未進行座標更新之第5圖的行車路線品質。 4照第1及6 ®所示，本發明第―實施例之物流 品求點還原步驟S13 ’其係將各合併需求點3還原為真正 3抓而求點12座標及數量，並依據先前完成之該初始 订路、.表進-步規劃各物流需求點U之最終行車路線。, in the combined demand point 3, the maximum value of the Χ coordinate and the difference between the large value of the Υ seat and the minimum value of the γ coordinate in I. And · see Figure 4, when by the above, and After the demand point 3, the coordinates can be advanced, and the new combined demand points 3, which are updated after the new coordinates are updated, are selected, such as joining, joining, and merging into three. The basis of the action. Since the "saving method" has the same effect as the kiss: the quality of the solution, it is possible to establish an initial driving route ": the first skill 7 is no longer described here", and after the second learning, the initial driving route is restored. The original coordinates of each merged demand point 3. P = is the map of the driving route established by the coordinates of each merged demand point 3: re-use ^ method"; Ϊ Combine the coordinates of demand point 3 and directly use the schematic diagram of the driving route that is obtained. Therefore, when comparing the * and 5 maps, it can be clearly seen that the driving route quality of Figure 4 (distance = is better than the driving route quality of Figure 5 without the coordinate update. 4 Photo 1 and 6 ® As shown in the first embodiment of the present invention, the logistics product point-reduction step S13' restores each merged demand point 3 to a true 3 grab and seeks a 12-point coordinate and quantity, and according to the previously completed initial round-trip, . The table advances and steps to plan the final driving route of each logistics demand point U.
PK10411 07J0&/U 10 200907833 例如：區域 合併需求點3，路線包含有A1、A2、A3三個 需求點】^ =合併需求點3還原後具有二個物流 點12 ;以及^二需未點3 原後具有三個物流需求 19 ^ 5併需求點3還原後亦具有+ =日發明步驟阳於局部關區 劃作業。該七前述七個物流需求點12進行路線規 較佳係藉由如、^需求點12之行車路線規劃方式，其 等啟發料」或後述「_群聚演算法」 區域B、t 輯A之較佳行車路線（其他如 該行車路線^目^行車路線求解方式亦同）。最後即完成 路線。 ' ^作業，以獲得較佳物流配送之最終行車 -I 一本土明第二實施例之商務物流途徑建立方法，其包 "> 舄求點合併步驟S21、一初始路彳f建立步驟S22 /亍車路彳t進階更新步驟§23及—物流需求點還原步驟 。其中第二實施例之S21、S22及S24步驟係分別與 相對，第1施例之S11' S12 A S13步驟大致相同，僅 在於完成該初始路徑建立步驟S22後，係配合計算該初始 路從之總運送成本，故本發明第二實施例之S21 ' S22及 S24步驟之執行方式於此不再贅述。另外，該行車路徑進 階更新步驟S23主要係以「螞蟻群聚演算法（Ant Colony Optimization ’ ACO)」為實作基礎，以充分利用該螞蟻群 聚演算法求解速度快及正確性高之特性，分別進行數個迭 代之行車路徑選擇，用以達到降低行車成本，以及更進一 PK10411 07/08/14 200907833 =義車:下線規劃品質之目的。—^ 'if g〇 otherwise lf s^Jk(r) otherwise arE niax {[r(r ^\]a r S S：^k(^,s)PK10411 07J0&/U 10 200907833 For example: regional consolidation demand point 3, the route contains three demand points A1, A2, A3] ^ = merge demand point 3 has two logistics points 12 after reduction; and ^2 requires no point 3 After the original, there are three logistics requirements of 19 ^ 5 and the demand point 3 is restored after the + = day invention step is positive for the partial closing operation. The seven above-mentioned seven logistics demand points 12 are preferably routed by the route planning method of the demand point 12, etc., or the "_ grouping algorithm" area B, t series A Better driving route (others are the same as the driving route ^^^ driving route solving method). The route is completed at the end. ' ^Operation, to obtain the final driving of better logistics distribution - I. A method for establishing a business logistics route of the second embodiment of the local, the package "> request point combining step S21, an initial path f establishing step S22 / 亍 彳 进 t advanced update step § 23 and - logistics demand point reduction steps. The steps S21, S22, and S24 of the second embodiment are respectively the same as the steps of S11' S12 A S13 of the first embodiment, except that after the initial path establishing step S22 is completed, the initial path is calculated. The total shipping cost, so the execution manner of the steps S21 'S22 and S24 of the second embodiment of the present invention will not be described herein. In addition, the driving route advanced updating step S23 is mainly based on the "Ant Colony Optimization 'ACO" algorithm, so as to make full use of the ant colony clustering algorithm to solve the problem of high speed and high accuracy. , respectively, a number of iterative driving route selection, in order to reduce the cost of driving, and further into a PK10411 07/08/14 200907833 = car: the purpose of planning quality offline. —^ 'if g〇 otherwise lf s^Jk(r) otherwise arE niax {[r(r ^\]a r S S:^k(^,s)
0 ••(2) 一^ 甘 士 、》 otherwise jr為人工螞_目前 -目的地位置^為—個 在二置/為人工螞蟻至下 )，其係介於0到i之門I均4分配（㈣崎Dlstributl〇n 或等於"夺，係採用舒、+. u f㈣要麥數，當㈧大於 :二夺，則採用前述公式(2)之 ^之= 洛蒙值，係為路徑㈣之 運^則。如)為費 對重要參數（權重），式函數，"為啟發式函數之相 /吸、櫂董j，其係針對費洛 相對重要參數（顧），其^為啟發式函數之 巧(0為第々隹人j轉録二’、:，/ML砗求點之間的距離； 需求點Λ機率㈣於一物流需求點广選擇到下一個物流 又，該螞蟻群聚演算法之費 式」係為 '、⑽—神，,)=^ 路輕之費洛蒙初始值，· ρ為G到1之間費、、各/_二為各 稱為蒸發係數。前述「區域更新公式、數’又 = 2㈣洛_高的频’造翁車路線落 4取仏g形，而無法跳脫出該區織最佳解。另外，該 馬蟻群聚演算之費洛蒙濃度的「全域更新公式」係為、、 PK10411 〇7/〇8/14 —12 200907833 目的在於祕_加強，_行車路線上 需求點3⑼’麵會再被射，糾剌更佳之行車路線 〇 蟻以=2:係=電腦系統設定數個人工螞 、f夂八Β 4」絲礎，且於該電腦核設定前 述各公式令之相闕參數，並以一定 作為各—蝴之二 二蟻可隨機由物流中心、11或各合併需求 佳行二’。1^^1)及公式⑺之_找出較 尋找出下—二二3更1 〜系於各人工碼蟻 點3 」係於各人工瑪蟻服務完所有合併需求 ^ 即進仃全域性的費洛蒙濃度更新。 ’k點3德，月亦可於各人工碼犧拜訪過所有合併需 線是否較佳心 之合併需求點3做=其： 性的費洛^ ^ /同樣將該代之最佳行車路線做全域 改盖更新。猎此’即可透過前述「2-_」來 :蓋_聚演算法」所建構之行車路線，且使用「2 :細後，純車路線仍必須料容量限制 過數個迭代之演化過程後，係分別計算各代之行 ΡΚ10411 07/08/14 200907833 車路線的總運送成本，並與前述該初始路徑之總運送成本 相互比較，以留下一組最佳之行車路線，再依據該行車路 線執行該物流需求點還原步驟％4,即可完成該行車路線 之規劃作業，以獲得較佳物流配送之最終行車路線。 、如上所述s相較於習知行車路線規劃方法，其具有 套進步降低其行車路線規劃之時間成本，以及所規劃 π行車路仅不佳專缺點。本發明係利用如等資 ，二群决异法’將相鄰之數個物流需求點Η合併歸屬為 L ^組2，再依據各群組2設定數個合併需求點3，以 政簡化欲排疋之行車路線，進而可大幅減少後續規劃行 =之時間成本。另外，係配合使用「節省法」初步規 ^ 1騎車路線，以便依制初始行車路線規劃及還 :取終之行車路線，故可纽提升行車路線規劃品質。再 収可加人「碼蟻群聚演算法」為實作基礎，並 達j〇Pt」’以更進一步尋求更佳之行車路線，以0 ••(2) 一^甘士,》 otherwise jr is artificial _ _ current-destination position ^ is one in two sets / for artificial ants to the bottom), the system is between 0 to i the door I average 4 Distribution ((4) Saki Dlstributl〇n or equal to " win, use Shu, +. u f (four) to be the number of wheat, when (eight) is greater than: two, then use the above formula (2) ^ = Lomon value, the path (4) The operation ^. For example, as the important parameter (weight), the function, " is the phase of the heuristic function / suck, 棹 Dong j, which is for the relatively important parameter of Fei Luo (Gu), its ^ The skill of the heuristic function (0 is the second person's transcript 2', :, the distance between the /ML pleading points; the demand point Λ probability (4) in a logistics demand point wide selection to the next logistics again, the ant colony The fee-based algorithm of the clustering algorithm is ', (10)-God,,) =^ The initial value of the pheromone of the light, · ρ is the fee between G and 1, and each /_ is called the evaporation coefficient. The above-mentioned "regional update formula, number" = 2 (four) Luo _ high frequency 'making Weng car route falls 4 to take the g shape, and can not jump out of the best solution of the region. In addition, the horse ant colony calculation fee The “global update formula” of Lomon concentration is, PK10411 〇7/〇8/14 —12 200907833 The purpose is to secretize _ strengthen, _ the driving route on the demand point 3 (9) 'face will be shot again, correcting the better driving route The ants use the =2: system = computer system to set a number of individual workers, f夂 gossip 4" silk, and set the parameters of the above formulas in the computer core, and as a certain Ants can be randomly selected by the logistics center, 11 or each merged demand. 1^^1) and formula (7) _ find out more than - 2 2 3 more 1 ~ tied to each artificial code ant point 3" is attached to each artificial ant service all merge requirements ^ that is to enter the global The pheromone concentration is updated. 'k points 3 de, the month can also be used in each artificial code to visit all the mergers required to be better than the combined demand point 3 do = its: sexual Fei Luo ^ ^ / also the best driving route for the generation The global update is updated. Hunting this can be done through the above-mentioned "2-_": the driving route constructed by the cover_gathering algorithm, and using "2: after the fine, the pure car route still has to be limited by the evolution of several iterations. Calculate the total shipping cost of each generation of the 10411 07/08/14 200907833 vehicle route, and compare it with the total shipping cost of the initial path to leave a set of best driving routes, and then according to the driving route. By executing the logistics demand point restoration step %4, the planning operation of the driving route can be completed to obtain the final driving route of the better logistics distribution. As described above, compared with the conventional driving route planning method, it has a set of progress. The time cost of reducing the route planning of the driving route and the planned π driving route are only poor. The invention uses the equal grouping method, and the two groups of different methods are used to merge the adjacent logistics demand points into L ^ Group 2, and then set a number of combined demand points 3 according to each group 2, so as to simplify the driving route to be exhausted, thereby greatly reducing the time cost of the subsequent planning line =. In addition, the use of "saving method" Preliminary rules ^ 1 cycling route, in order to comply with the initial driving route planning and also: take the final driving route, so can improve the planning quality of the driving route. Re-acquisition of the "code ant colony clustering algorithm" as the basis for the implementation, and up to j〇Pt"' to further seek for better driving routes,
效。^仃車成本及更進—步提升行車路線關品質之功 ]}、雖然本發明已利用上述較佳實施例揭示，然立並 任何熟習此技藝者在不脫離本發明之精 本發二細進行各種更動與修改仍屬 附之申請專利範圍所界;者=本备明之保護範圍當視後 PK10411 07/08/14 14 — 200907833 【圖式簡單說明】 第1圖：本發明第一實施例之商務物流途徑建立方法 的步驟流程示意圖。 第2圖：本發明第一實施例之商務物流途徑建立方法 之物流需求點分佈示意圖。 第3圖：本發明第一實施例之商務物流途徑建立方法 執行步驟S11之示意圖。 第4圖：本發明第一實施例之商務物流途徑建立方法 執行步驟S12之行車路線示意圖。 第5圖：本發明第一實施例之商務物流途徑建立方法 未執行步驟S12之行車路線示意圖。 m 第6圖：本發明第一實施例之商務物流途徑建立方法 執行步驟S13所還原之最終行車路線示意圖。 第7圖：本發明第二實施例之商務物流途徑建立方法 的步驟流程示意圖。 第8圖：本發明第二實施例之商務物流途徑建立方法 使用「2-opt」交換合併需求點之規則參考圖（一）。 第9圖：本發明第二實施例之商務物流途徑建立方法 使用「2-opt」交換合併需求點之規則參考圖（二）。 【主要元件符號說明】 12物流需求點 3 合併需求點 11物流中心 2 群組 3’合併需求點 PK10411 07/08/14 '15 一 200907833 s】i物流需求點合併步驟 S13物流需求點還原步驟 S21物流需求點合併步驟 S12初始路徑建立步驟 S22初始路徑建立步驟 S23行車路徑進階更新步驟S24物流需求點還原步驟 PK10411 07/08/14 16 —effect. ^ 仃 成本 成本 及 成本 成本 成本 成本 成本 ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] ] The various modifications and modifications are still within the scope of the patent application scope; the scope of protection of this specification is PK10411 07/08/14 14 — 200907833 [Simplified illustration] Fig. 1: First embodiment of the present invention Schematic diagram of the steps of the method for establishing a business logistics route. Fig. 2 is a schematic view showing the distribution of logistics demand points in the method for establishing a business logistics route according to the first embodiment of the present invention. Figure 3: Method for establishing a business logistics route according to the first embodiment of the present invention. Figure 4: Method for establishing a business logistics route according to the first embodiment of the present invention A schematic diagram of the driving route of step S12. Figure 5: A method for establishing a business logistics route according to the first embodiment of the present invention. A schematic diagram of the driving route of step S12 is not performed. m Fig. 6: Method for establishing a business logistics route according to the first embodiment of the present invention A schematic diagram of the final driving route restored in step S13. Figure 7 is a flow chart showing the steps of the method for establishing a business logistics route according to the second embodiment of the present invention. Figure 8: Method for establishing a business logistics route according to a second embodiment of the present invention A rule reference chart (1) for exchanging merge demand points using "2-opt". Fig. 9 is a diagram showing a method for establishing a business logistics route according to a second embodiment of the present invention. The rule for exchanging demand points using "2-opt" is referred to (2). [Main component symbol description] 12 Logistics demand point 3 Consolidation demand point 11 Logistics center 2 Group 3' merge demand point PK10411 07/08/14 '15 A 200907833 s] i logistics demand point consolidation step S13 logistics demand point reduction step S21 Logistics demand point combining step S12 initial path establishing step S22 initial path establishing step S23 driving path advanced updating step S24 logistics demand point restoring step PK10411 07/08/14 16 —