  Supply chain management is an integrated approach for planning and
controlling materials, information, and finances as they move in a process
which begins from suppliers and ends with customers in forward approach. As
distribution network planning is strategically done, the related decisions
should be optimized. This supply chain planning involves transportation, the
location of facilities, and inventory control decisions. This study is a new
approach for considering customers' differentiation in an integrated model to
location-allocation and inventory control supply chain. The proposed model is
multi-product, single-period and with stochastic demands. Additionally,
warehouses have multilevel capacity limitation. For more reality, the
probability of transportation through different vehicles, different
transportation capacity, and transportation costs are also taken into the
consideration. The customers are divided into two strategic and nonstrategic
groups by adopting the critical level policy. The exact calculation method is
employed for small scale instances while hybrid meta-heuristic algorithms
(Genetic and Simulated Annealing) developed for real samples. Efficiency and
quality of solutions are examined via the ANOVA to report proper and near
optimum solution. Finally, sensitivity analysis is carried out for different
instances to evaluate the effect of different indexes on the duration of CPU
time and values of the objective function.
