Research on the time optimization model algorithm of Customer Collaborative Product Innovation
Abstract: To improve the
efficiency of information sharing among the innovation agents of customer
collaborative product innovation and shorten the product design cycle, an
improved genetic annealing algorithm of the time optimization was presented.
Design/methodology/approach: Based on the analysis of the objective relationship
between the design tasks, the paper takes job shop problems for machining model
and proposes the improved genetic algorithm to solve the problems, which is
based on the niche technology and thus a better product collaborative
innovation design time schedule is got to improve the efficiency. Finally,
through the collaborative innovation design of a certain type of mobile phone,
the proposed model and method were verified to be correct and effective.
Findings and Originality/value: An algorithm with obvious advantages in
terms of searching capability and optimization efficiency of customer
collaborative product innovation was proposed. According to the defects of the
traditional genetic annealing algorithm, the niche genetic annealing algorithm was
presented. Firstly, it avoided the effective gene deletions at the early search
stage and guaranteed the diversity of solution; Secondly, adaptive double point
crossover and swap mutation strategy were introduced to overcome the defects of
long solving process and easily converging local minimum value due to the fixed
crossover and mutation probability; Thirdly, elite reserved strategy was
imported that optimal solution missing was avoided effectively and evolution
speed was accelerated.
Originality/value: Firstly, the improved genetic simulated annealing
algorithm overcomes some defects such as effective gene easily lost in early
search. It is helpful to shorten the calculation process and improve the
accuracy of the convergence value. Moreover, it speeds up the evolution and
ensures the reliability of the optimal solution. Meanwhile, it has obvious
advantages in efficiency of information sharing among the innovation agents of
customer collaborative product innovation. So, the product design cycle could be
shortened.
Keywords: Genetic simulated
annealing algorithm; Niche; Customer Collaborative Product innovation
scheduling; Simulation
Author: Guodong Yu, Yang Yu,
Qingsong Xing, Fei Li
Journal Code: jptindustrigg140028
