Hyper-heuristics are emerging methodologies that perform a search over the space of heuristics to solve difficult computational optimization problems. There are two main types of hyper-heuristics: selective and generative hyper-heuristics. An online selective hyper-heuristic framework manages a set of low level heuristics and aims to choose the best one at any given time using a performance mea...

This paper presents a multi-objective mathematical model which aims to optimize and harmonize supply chain reduce costs, improve quality, achieve competitive advantage position using meta-heuristic algorithms. The purpose of optimization in this field is increase quality customer satisfaction production time related prices. present research simultaneously optimized the multi-product multi-perio...

09:30 Tristan Cazenave, Marek Cornu, Daniel Vanderpooten A two-phase meta-heuristic applied to the Multi-objective Traveling Salesman Problem Recently, a number of hybrid meta-heuristics have been successfully applied on different problems like the MO Traveling Salesman Problem (TSP), the MO Multidimensional Knapsack Problem and the MO Flow-shop Scheduling Problem. We present a method providing...

With data centers, end-users can realize the pervasiveness of services that will be one day the cornerstone of our lives. However, data centers are often classified as computing systems that consume the most amounts of power. To circumvent such a problem, we propose a self-adaptive weighted sum methodology that jointly optimizes the performance and power consumption of any given data center. Co...