Urban Rail Transit Rolling Stock Scheduling Optimization with Shared Depot

Feng, Jia; Li, Guowei; Shi, Yuxin; Li, Zheng-zhong; Liu, Shanshan

doi:10.3390/su142215075

Cited by 1 publication

(2 citation statements)

References 18 publications

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“…Judge whether the time window meets the distribution requirements. If it does not, perform step (7). Otherwise, perform step (8);…”

Section: Implementation Scheme Of An Improved Ant Colony Algorithmmentioning

confidence: 99%

“…Over the past two years, as industrial automation and intelligent manufacturing have become mainstream trends, the AMR industry has embraced important development opportunities [1]. At present, the technologies affecting the deep development of AMR technology mainly include navigation technology [2,3], wireless sensor networks [4], control technology [5], and the development of a scheduling system and path planning platform [6,7]. A good scheduling system and path planning platform can ensure that the AMR can still ensure the normal operation of the warehouse logistics system; on the other hand, enterprises can achieve cost reduction and increased efficiency and can reduce consumption while achieving sustainable development.…”

Section: Introductionmentioning

confidence: 99%

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Semi-Open Multi-Distribution Center Path Planning with Time Windows

Song

2023

Sustainability

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A well-planned robot dispatching platform reduces costs and increases efficiency for companies while also reducing carbon emissions and achieving sustainable development. At the moment, the solution to the difficulty of warehouse logistics is use of multiple distribution centers with autonomous mobile robots (AMR). To solve this problem, this paper establishes a semi-closed model of multiple distribution centers, considering the number of cycles and the number of vehicles. An improved ant colony algorithm is proposed to improve the heuristic function based on the node distance relationship to improve the quality of path search. Dynamic variable pheromone concentration and volatility factors are set to accelerate the convergence speed of the algorithm while effectively reducing the problem of the premature algorithm. The traditional ant colony algorithm and the improved ant colony algorithm are used to solve the established model. In addition, the results show that the traditional ant colony algorithm has a certain rate of dominance in the single-day cost of the closed distribution model, but the overall comprehensive cost is lower than that of the improved ant colony algorithm. The single-day cost of the semi-open multi-distribution center logistics and distribution model is lower than that of the closed multi-distribution center logistics and distribution model, and the 7 day average cost is reduced by 12%. The improved ant colony algorithm can save about 119 kWh of electricity under the same target volume requirement, which achieves the company’s goals of cost reduction and increased efficiency, as well as green and sustainable development.

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“…Judge whether the time window meets the distribution requirements. If it does not, perform step (7). Otherwise, perform step (8);…”

Section: Implementation Scheme Of An Improved Ant Colony Algorithmmentioning

confidence: 99%