When arriving at the airport,flight needs to be served by special *** at the dynamic time window scheduling problem of airport refueling vehicles,this paper establishes a vehicle routing problem model with time window...
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ISBN:
(数字)9789887581536
ISBN:
(纸本)9781665482561
When arriving at the airport,flight needs to be served by special *** at the dynamic time window scheduling problem of airport refueling vehicles,this paper establishes a vehicle routing problem model with time window to minimize the operating ***,a multi-strategy genetic algorithm is designed to gain the solve time window scheduling problem,which employs the crossover based on particle swarm optimization to accelerate the early search capability,and the local search method based on simulated annealing to increase the local optimization *** aiming at dynamically adjusting vehicle routes on the basis of static scheduling,a local replanning strategy based on a dynamic time window is introduced,which uses the original route matching and rescheduling *** results show that the multi-strategy hybrid algorithm can effectively reduce the number of routes and vehicles the airport *** different scales' dynamic changes of time windows,the algorithm could enable vehicles to still meet time constraints and effectively minimize the change of routes.
As vital energy-consuming equipment of the industrial cooling circulating water system, scientific scheduling of the circulating water pump station (CWPS) is crucial for energy conservation. In this paper, we propose ...
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As vital energy-consuming equipment of the industrial cooling circulating water system, scientific scheduling of the circulating water pump station (CWPS) is crucial for energy conservation. In this paper, we propose a genetic optimisation model. An optimal scheduling model is established to minimise power consumption, considering the production demand and pumps' high-efficiency area constraints. Branch water pipe characteristic curves are introduced to determine the accurate pump operating condition. A multi-strategy genetic algorithm (MSGA) is proposed for the strict production demand constraints and the deficiency of complex constraint processing techniques. The MSGA screens feasible solutions by simply judging and achieves infeasible region information utilisation and search strategy adaptive adjustment by the sequence-based fitness construction, multi-mutation and adaptive control parameters strategies. The case results show that the proposed model can significantly reduce power consumption while improving pump efficiency over the original operation scheme of CWPS.
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