The integrated optimization method for production and distribution planning in supply chain is studied. Decisions
of different functions such as demand allocating, production scheduling, distribution consolidating and vehicle routing are
integrated for a simultaneous optimization. The factor of time windows restrictions is used to coordinate the optimization
process of all sub-models, which can attain higher service level and lower operational costs. An integrated approach
combining tabu search and genetic algorithm is developed to solve the problem. Two experiments adopting integrated
approach and decoupled approach respectively are conducted on two problems with different scales, and the results conform
the substantial advantage of the integrated approach. Finally, sensitivity analysis on penalty parameters indicates that, the
factor of time windows restrictions has significant influence on operational costs.