Research On Optimization Of Precast Concrete Component Transportation Vehicle Schedule Based On Improved Artificial Fish Swarm Algorithm

In recent years,in the background of industrialization of buildings,prefabricated precast concrete(PC)component manufacturers is ushering in new development opportunities.Different from ordinary cargo transportation,PC components have higher requirements in transportation vehicles,transportation personnel,transportation time limits and transportation specialization.However,most PC component manufacturers currently rely on experience to make transportation vehicle scheduling solutions.lacking systematic and reasonable planning.As a result,the PC component transportation has problems such as “high cost,low efficiency,and can not be delivered to the construction site on time”.In severe cases,it even affects the construction plan.Therefore,how to establish a PC component transportation scheduling model that can meet construction requirements and minimize the transportation cost of the component manufacturers is the core research content of this paper.Based on these,the main work done in this paper is as follows:1 For the One-to-many mode of a PC component factory serves multiple construction sites,in the premise of the demand of the construction sites is determined and the transportation vehicles of the component factory are limited,established the multi-objective transportation vehicle scheduling model with the minimum total transportation cost,the minimum total number of transports required,and the shortest waiting and delay time.Among them,the total transportation cost includes the loading and unloading cost of the PC component,the transportation cost of the vehicle,and the penalty cost that does not satisfy the soft time window constraint.The transportation cost is composed of the vehicle activation cost,the vehicle-based load-based departure and the no-load return fuel cost.The penalty cost is positively correlated with the length of time that the vehicle arrival time exceeds the time window constraint.2 The PC component transportation scheduling problem is a typical NP-hard problem,and the artificial fish swarm algorithm can effectively solve this kind of problem effectively.However,the basic artificial fish swarm algorithm has some limitations.Aiming at these problems,this paper combines the characteristics of PC component transportation scheduling to improve the basic artificial fish swarm algorithm.First of all,for the limitation of slow convergence speed and lowering precision of the algorithm in the later stage of the algorithm,the iteration numberformula and the step coefficient ? are used to dynamically adjust the field of view and the step size of the artificial fish,so that the field of view gradually decreases with the increase of the number of iterations,and the step is proportionally reduced with the field of view to prevent prematurely falling into local extremum,improving the convergence efficiency and the precision of optimization.Secondly,ignore the influence of the congestion factor which can simplified operation with the reduce of parameters;the jumping behavior of artificial fish is introduced to improve the ability of artificial fish to jump out of local extremum;the swallowing behavior of artificial fish was introduced to solve the algorithm increase amount of calculation.Finally,the performance of the AFSA and the IAFSA was simulated by Matlab R2014 b using four standard test functions,which proved the optimization effect of the IAFSA.3 Finally,the model is applied to the transportation dispatch of a PC component factory in Qijiang District,Chongqing.The AFSA and the IAFSA are used to solve the examples,and it proves the practicability and applicability of the PC component transport vehicle scheduling optimization model.It is also verified that the improved artificial fish swarm algorithm is more effective than the basic artificial fish swarm algorithm in improving the algorithm convergence speed,improving the optimization precision and enhancing the global search ability.This paper provides an optimization scheme for the transportation scheduling of PC components.I hope that the research of this paper will improve the transportation efficiency of PC component enterprises,reduce transportation costs and improve customer satisfaction.It also provides practical reference for the study of vehicle scheduling optimization in other fields of transportation industry.