Optimization and simulation for design of multi-objective, multi-echelon supply chain system
The study of the effect of redistribution strategy, aggregation, on a multi-echelon supply chain network by managing demand volatility is discussed in this research. For this an operational supply chain design is considered. Multi-echelon network consisting of manufacturing plants, distribution centers, warehouses, and retailers is used to develop the case study. Aggregation strategy was analyzed in the context of single product and multi-product for a multi-period production problem under demand uncertainty. Product sourcing between echelons and distribution strategies are considered for the study. Objective was to use the redistribution strategy to optimize the objective functions for the network. The objective functions include minimization of total cost, minimization of overage and stock-out conditions, and maximization of the customer service level. The total cost function includes product flow, transportation cost and distance cost. The mathematical formulation is carried out in Mixed Integer Linear Programming (MILP) with the help of Generic Algebraic Modeling System (GAMS) and compared using AnyLogic simulation package. Problem formulation considers three type of demand based on volatility and uncertainty cases as high, medium, and low. The research is divided into three main phases. The first phase of the dissertation discusses an optimal multi-echelon supply chain network for single product using aggregation strategy. While the second phase discusses an optimal multi-echelon supply chain network for multi-product using aggregation strategy. Final phase of the dissertation discusses use of aggregation strategy for a single product using simulation.
Thesis (Ph.D.)-- Wichita State University, College of Engineering, Dept. of Industrial, Systems and Manufacturing Engineering