Analysing the factors that influence the Pareto frontier of a bi‐objective supply chain design problem

In this paper a bi‐objective multi‐product model for the design of a production/distribution supply chain logistic network with four echelons is considered. The proposed optimization model minimizes the total cost of the network (including the fixed cost to open facilities and the transportation costs between them) and the total CO 2 emissions. Five factors (network size, product complexity, cost variability, CO 2 emissions generation and over‐capacity) are considered for the experimental framework. The problem is solved using the ε‐constraint method and the resulting Pareto frontiers (PF) are characterized using five new metrics specifically developed for analysing how those factors affect the resulting optimal configurations. The results show that over‐capacity and product complexity are the two most influential factors regarding the characteristics of the PF, and that their effects are in the same direction: more complexity and capacity mean a wider set of optima alternatives, some close to the ideal point, and in general with a smaller number of links used.