Combined Use of Mathematical Optimization and Design of Experiments for the Maximization of Profit in a Four‐Echelon Supply Chain

Abstract

This paper develops a location-allocation model to optimize a four-echelon supply chain network, addressing manufacturing and distribution centers location, supplier selection and flow allocation for raw materials from suppliers to manufacturers, and finished products for end customers, while searching for system profit maximization. A fractional-factorial design of experiments is performed to analyze the effects of capacity, quality, delivery time, and interest rate on profit and system performance. The model is formulated as a mixed-integer linear programming problem and solved by using well-known commercial software. The usage of factorial experiments combined with mathematical optimization is a novel approach to address supply chain network design problems. The application of the proposed model to a case study shows that this combination of techniques yields satisfying results in terms of both its behavior and the obtained managerial insights. An ANOVA analysis is executed to quantify the effects of each factor and their interactions. In the analyzed case study, the transportation cost is the most relevant cost component, and the most relevant opportunity for profit improvement is found in the factor of quality. The proposed combination of methods can be adapted to different problems and industries.

Modelling of just-in-time distrubution network under raw material quality and time constraints

“…Excel Solver program was used to solve the proposed model and scenario analysis. Vera et al [15] propose a mixed-integer linear programming model that analyzes the effects of capacity, quality, delivery time, and interest rate factors on supply chain profit. In the model, the cost of poor quality was studied for the quality factor and process adequacy indices were used.…”

Decision Optimization of Four-Level Supply Chain with the Participation of Two-Echelon Logistics Service Providers under Different Power Structures

“…On this basis, Hamed et al [26] constructed a multiobjective integer programming model with the smallest cost and the best service level to study the optimal product quality level decision of the four-level supply chain. Olivares et al [27] used a mixed-integer linear programming model to study the location selection plan to maximize the profit of the four-level supply chain system from the perspective of distribution center location selection. Hasanov et al [28] studied the optimal production and inventory decisions of a four-level closed-loop supply chain with the goal of minimizing the total cost of a closed-loop supply chain.…”