【摘要】：隨著近些年物流企業(yè)的快速發(fā)展,企業(yè)對(duì)減少成本的期望越來越強(qiáng)烈,非常需要針對(duì)車輛分派問題進(jìn)行研究。車輛路徑問題正是對(duì)此類問題進(jìn)行研究,早期大多數(shù)研究主要集中在約束車輛路徑問題,但是約束車輛路徑問題的局限性抑制了它的實(shí)用性。動(dòng)態(tài)車輛路徑問題是在約束車輛路徑問題的基礎(chǔ)上,通過取消預(yù)知全部顧客需求的限制條件,從而更加符合實(shí)際情況,但同時(shí)也比約束車輛路徑問題更難求解最優(yōu)解。目前動(dòng)態(tài)車輛路徑問題的研究還不多,而針對(duì)更符合實(shí)際情況的帶時(shí)間約束的動(dòng)態(tài)車輛路徑問題的研究更少,非常需要針對(duì)此類問題建立模型并設(shè)計(jì)高效的算法。本文通過對(duì)帶時(shí)間約束的動(dòng)態(tài)車輛路徑問題建立相應(yīng)數(shù)學(xué)模型,提出混合算法(模擬退火算法和遺傳算法)的解決方案,并在此基礎(chǔ)上,實(shí)現(xiàn)帶時(shí)間約束的動(dòng)態(tài)車輛調(diào)度系統(tǒng)的設(shè)計(jì)與開發(fā)。本文提出的混合算法將解決方案設(shè)置為兩個(gè)階段:第一個(gè)階段發(fā)揮模擬退火算法的快速性,獲取預(yù)備最優(yōu)解集;第二個(gè)階段發(fā)揮遺傳算法的高效性,并使用第一個(gè)階段的預(yù)備最優(yōu)解集作為種群,在處理遺傳算法中針對(duì)選擇操作、交叉操作、變異操作提出了靈活的解決方案,最終獲得最優(yōu)解。通過與一般的遺傳算法和模擬退火算法進(jìn)行對(duì)比實(shí)驗(yàn),證明了本論文算法的優(yōu)越性。另外,基于本文混合算法開發(fā)的帶時(shí)間約束的動(dòng)態(tài)車輛調(diào)度系統(tǒng)包含了三個(gè)階段,即前臺(tái)數(shù)據(jù)輸入,后臺(tái)數(shù)據(jù)運(yùn)算,以及通過結(jié)合百度地圖應(yīng)用程序界面來展示運(yùn)算結(jié)果。
[Abstract]:With the rapid development of logistics enterprises in recent years, the expectation of cost reduction is becoming stronger and stronger, so it is very necessary to study the vehicle assignment problem. The vehicle routing problem is just to study this kind of problem. In the early years, most of the researches focused on the constrained vehicle routing problem, but the limitation of the constrained vehicle routing problem restrained its practicability. On the basis of constrained vehicle routing problem, dynamic vehicle routing problem (DMPS) is more in line with the actual situation by canceling the constraints that predict all customer needs, but at the same time, it is more difficult to solve the optimal solution than the constrained vehicle routing problem. At present, there are not many researches on dynamic vehicle routing problem, but there is less research on dynamic vehicle routing problem with time constraint, which is more suitable to the actual situation. It is very necessary to build a model and design efficient algorithm for this kind of problem. In this paper, the mathematical model of dynamic vehicle routing problem with time constraint is established, and the solution of hybrid algorithm (simulated annealing algorithm and genetic algorithm) is proposed. Design and development of dynamic vehicle scheduling system with time constraints. The hybrid algorithm proposed in this paper sets the solution into two stages: the first stage takes advantage of the rapidity of the simulated annealing algorithm to obtain the preparatory optimal solution set; In the second stage, the high efficiency of genetic algorithm is brought into play, and the preoptimal solution set of the first stage is used as the population. In dealing with genetic algorithm, a flexible solution is put forward for the selection operation, cross operation and mutation operation. Finally, the optimal solution is obtained. Compared with genetic algorithm and simulated annealing algorithm, the superiority of this algorithm is proved. In addition, the dynamic vehicle scheduling system with time constraints is developed based on the hybrid algorithm in this paper, which includes three stages: foreground data input, background data operation, and displaying the results by combining the Baidu map application program interface.
【學(xué)位授予單位】：哈爾濱工業(yè)大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：TP311.52;TP18

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本文編號(hào)：2299773