A new algorithm for linearly constrained c-convex vector optimization with a supply chain network risk application
Vector optimization is studied. A proximal point algorithm is proposed for vector optimization. The global and local convergence results for the new algorithm are presented. The efficiency of the new algorithm is shown by an application to a supply chain network risk management problem.
c-convex proximal point algorithm supply chain network risk management multiple objective programming pareto optimum