本文關(guān)鍵詞： 倉儲物流機器人 揀選作業(yè) 路徑規(guī)劃 旅行商問題 遺傳算法 A*算法　出處：《中北大學(xué)》2017年碩士論文　論文類型：學(xué)位論文

【摘要】：在電子商務(wù)的背景下,倉儲物流配送具有“品種多、批量小、批次多、周期短”的特點。隨著電子商務(wù)的快速發(fā)展、顧客對消費體驗重視程度的提高以及人力成本的上升,傳統(tǒng)的倉儲物流技術(shù)已經(jīng)越來越難以適應(yīng)物流配送的需要,以人工智能技術(shù)為支撐的倉儲物流機器人技術(shù)開始被應(yīng)用到倉儲物流領(lǐng)域,而如何為倉儲物流機器人在倉庫中進行高效實時的揀選路徑規(guī)劃是迫切需要解決的問題。針對如何實現(xiàn)多倉儲物流機器人在揀選作業(yè)的過程中進行高效實時的路徑規(guī)劃問題,本文提出一套完整的解決方案。首先,根據(jù)倉庫以及倉儲物流機器人移動的特點建立一個靈活的倉庫模型并利用修正的A*算法實現(xiàn)單機器人單揀選點的路徑規(guī)劃。其次,根據(jù)批量揀選作業(yè)任務(wù)的特點,建立了以路徑總長度最小為優(yōu)化目標(biāo)的旅行商問題的數(shù)學(xué)模型,然后提出改進的自適應(yīng)遺傳算法解決旅行商問題并與修正A*算法相結(jié)合實現(xiàn)單機器人批量揀選的路徑規(guī)劃。再次,在考慮單倉儲物流機器人轉(zhuǎn)向時間、貨物揀選時間以及多倉儲物流機器人的位置沖突等待時間的前提條件下,引入時間代價對A*算法作進一步改進以實現(xiàn)多倉儲物流機器人批量揀選路徑規(guī)劃。最后,根據(jù)本文提出算法,利用.Net可視化編程技術(shù),建立了一個完整的倉儲物流機器人揀選路徑規(guī)劃仿真系統(tǒng)以用來驗證本文所提出算法的有效性,并分析了在是否考慮機器人避障的條件下不同機器人數(shù)量對多倉儲物流機器人批量揀選作業(yè)任務(wù)完成的時間、平均路徑長度以及路徑?jīng)_突協(xié)調(diào)的影響。
[Abstract]:Under the background of electronic commerce, warehousing logistics distribution has the characteristics of "variety, small batch, many batches, short cycle". With the rapid development of electronic commerce. With the increase of customer's attention to consumption experience and the increase of manpower cost, the traditional warehousing logistics technology has become more and more difficult to meet the needs of logistics distribution. The technology of warehouse logistics robot supported by artificial intelligence technology has been applied to the field of warehousing logistics. It is urgent to solve the problem of how to carry out efficient and real-time routing planning for warehousing logistics robot in warehouse, aiming at how to realize the efficient and real-time path of multi-warehouse logistics robot in the process of sorting. Path planning. This paper proposes a complete set of solutions. First of all. According to the characteristics of warehouse and warehouse logistics robot mobile, a flexible warehouse model is established, and a modified A* algorithm is used to realize the path planning of single robot picking point. According to the characteristics of batch sorting task, a mathematical model of traveling salesman problem with the minimum path length as the optimization objective is established. Then an improved adaptive genetic algorithm is proposed to solve the traveling salesman problem and combined with the modified A * algorithm to realize the path planning of single robot batch picking. Thirdly, the turning time of single warehouse logistics robot is considered. The cargo picking time and the location conflict waiting time of the multi-warehousing logistics robot are under the premise of the waiting time. Time cost is introduced to further improve the A* algorithm in order to realize bulk routing planning of multi-warehouse logistics robot. Finally, according to the algorithm proposed in this paper, using .Net visual programming technology. A complete routing path planning simulation system for warehouse logistics robot is established to verify the effectiveness of the proposed algorithm. The effects of different number of robots on the completion time, average path length and path conflict coordination of multi-warehouse logistics robots are analyzed.
【學(xué)位授予單位】：中北大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：TP242

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