BPGSA And Its Application In Equipment Inspection Forecast

In real life,with the engineering application demands continuously widened and searching for the further economic developments,people are depending on the technology furiously.For example,there are many NP(Non-deterministic Polynomial)complex problems in the fields of engineering,production planning and economic management.And there are more and more complicated optimization problems of many fields and the actual engineering problems are turning to large scales,nonlinear,strong constraints and high dimensions.All these increase the difficulty of problem solving a certain extent.Traditional optimization methods are hard to solve these problems and the results could not meet the goals as we expected.Therefore,exploring effective and reasonable optimization methods has become one of the contemporary study of active contents and hot topics.In order to solve the optimization problems with the actual productions,this thesis contrasts some different traditional heuristic algorithms upon the researches by a mass of scholars and experts at home and abroad,analyzing the limitations of the traditional heuristic algorithms.Aiming to improve the efficiency and accuracy of the non-integer programming problems,this paper realized a new algorithm(Binary Plant Growth Simulation Algorithm,BPSGA),which combines binary system with plant growth simulation algorithms to build a binary growth space.With the help of encoding and decoding,this algorithm realized the conversion to decimals and binary and designed a new binary growth pattern,which expanded application range of the integer programming to the non-integer programming.This paper uses the binary emulation plant growth simulation algorithm to solve different functions of high-speed of convergence contrasted with traditional plant growth simulation algorithms and genetic algorithm.The algorithm is hard to fall into local optimal solutions and it has the advantages of quickly converging on the global optimal solutions,proving the effectiveness of the algorithm.What the paper studies has important meanings and lessoning value of the solutions to non-integer programming problems with the help of effective technical means.Finally,in order to verify the algorithm's practicability,this paper censuses the special equipment's inspections in D city for nearly 10 years and uses the binary emulation plant growth simulation algorithm to fit and forecast the inspections from the past decade to the next five years.The maximum error of the fitting values are just 5.60%,verifying the validity and suitability of the algorithm upon solving the practical problems.According to the forecast,the special equipment's inspections in D city show a rising trend fluctuated in the next 5 years.Based on the research,this thesis put forward the corresponding advice and countermeasures of the working plans and production scheduling for the special equipment of inspections in D city.