Research On Radio And Television Transmission Task Allocation And Scheduling Optimization Based On Heuristic Intelligence Algorithm

The optimization problem of radio and television transmission task allocation and scheduling can be classified as a special scenario application of combinatorial optimization problem(COP).Currently,heuristic intelligent algorithms are widely used in the field of COP.However,for the specific scenario of radio and television transmission task allocation and scheduling,it is necessary to select suitable heuristic intelligent algorithms and reset the basic elements and specific operations of the algorithm to make it suitable for precise solution of the problem,thereby improving the accuracy and work efficiency of radio and television transmission task allocation and scheduling optimization.The paper takes the application of heuristic intelligent algorithms in COP as the theoretical research foundation,and takes the optimization of radio and television transmission task allocation and scheduling as the practical application scenario.The applicability improvement and parameter configuration optimization of heuristic intelligent algorithms are carried out,achieving the practical application effect of calculating the precise optimal solution of task allocation and scheduling through heuristic intelligent algorithms in the construction of intelligent systems for radio and television transmission stations.The paper focuses on in-depth research on the key technologies of task allocation and scheduling optimization,and proposes optimization models and evaluation methods for the problem of radio and television transmission task allocation and scheduling.On this basis,an improved genetic algorithm(IGA)and a discrete particle swarm optimization algorithm(DPSO)were proposed for the one-dimensional space task allocation problem.Aiming at the problem of two-dimensional space task scheduling and intelligent generation of Schedule,Schedule improved genetic algorithms(SIGA)and Schedule particle swarm optimization algorithms(SPSO)have been proposed.A heuristic intelligent algorithm application strategy based on disaster recovery theory is proposed to meet the calculation requirements of precise optimal solutions in practical application scenarios of system construction.The innovative work of the paper mainly includes the following four aspects:Firstly,proposed an optimization model and evaluation method for radio and television transmission task allocation and scheduling.A task allocation and scheduling optimization model and evaluation method suitable for heuristic intelligent algorithm solving are proposed to address the low level of quantitative calculation analysis and transmission effect evaluation in the current research field of intelligent systems for radio and television transmission stations.This method builds an evaluation model,constructs an effectiveness evaluation matrix from two dimensions:the sequence of transmitting devices and the sequence of task frequency bands,designs a fitness objective function,and achieves precise quantitative evaluation of algorithm calculation effectiveness.Finally,the effectiveness of the model and quantitative evaluation method was verified through enumeration,greed,and traditional genetic algorithms.Secondly,proposed IGA and DPSO for solving one-dimensional spatial task allocation problems.IGA based on cyclic exchange grouping for cross operation is proposed to address the issue of conflict handling in traditional genetic algorithms for solving specific COP.This algorithm fully considers the irrelevance of task allocation between adjacent device sequences in the radio and television transmission task allocation problem,and uses a loop tracking strategy to identify non continuous switching packets for crossover operations.Compared with traditional genetic crossover operations such as partial matching crossover,this crossover operation avoids gene conflict processing,and the offspring can fully inherit all the genes of the parent.Two hybrid algorithms are proposed to address the complex operation of particle swarm optimization algorithm(PSO)in solving COP.One is to establish a population based on genetic algorithm and PSO,replacing genetic selection operations with global optimization,particle optimization,and particle position;The second is based on PSO,proposing a discretization processing method based on probability selection model,which takes into account the position update balance in the three directions of particle inertia preservation,global optimization,and particle optimization at the population level,and replaces the particle position update operation with genetic crossover operation.DPSO is proposed to address the problem of difficult mathematical description of particle position update operations in particle swarm optimization.This algorithm is based on a probability selection model and replaces particle swarm optimization vector calculation with task swapping.Experiments have shown that the efficiency and computational accuracy of the DPSO and the IGA are superior to those of the hybrid intelligent algorithm.Thirdly,proposed SIGA and SPSO for solving two-dimensional spatial task scheduling and Schedule generation problems.SIGA is proposed for optimizing the scheduling of two-dimensional space tasks under the limited conditions of continuous execution of radio and television transmission tasks.The algorithm completes device level task exchange through cross operation and time slot level task exchange through mutation operation.SPSO is proposed,which adopts a bidirectional search alignment strategy in particle motion update operations,limiting the particle motion direction and target granularity within a time period,thereby increasing the accuracy of task scheduling exchange.The experiment shows that two heuristic intelligent algorithms can efficiently solve the problem of intelligent generation of Schedule.Fourthly,proposed a heuristic intelligent algorithm application strategy based on disaster recovery theory.To optimize the intelligent task allocation and scheduling of radio and television transmission stations in practical application scenarios,complete the simulation system design,and propose an intelligent algorithm application strategy based on disaster recovery theory.This strategy is based on the research results of the optimal parameter array testing of the two heuristic intelligent algorithms mentioned earlier.Three different sets of parameters are used to execute the SPSO and one set of parameters is used to SIGA by executing the Schedule.The simulation system experiment shows that compared with the precise calculation results of the branch and bound algorithm,this strategy can calculate the exact optimal solution.