Keynote Speakers



Most problems faced by logistics operators have been known for centuries, think of the Chinese postman problem, first formulated by Euler in 1736. These problems have the ugly characteristic of being combinatorial, that is, all the possible combinations of the decisions and variables must be explored to find a solution of the problem. Recently, to rapidly solve these problems, heuristics methods have been devised to explore only parts of the search space, concentrating in those parts that appear to promise a probable improvement of the solutions. One of the most recent and powerful heuristic is Ant-Colony Optimization (ACO). ACO is based on the observation that real ants find the optimal path between a food source and their nest food by depositing chemical traces (pheromones) on the floor. A computer analogy has been implemented where a large number of simple artificial ants are able to build good solutions to VRP problems via low-level based communications based on artificial pheromone. We present the basic ACO principles and we review the most recent researches in the VRP domain focusing on running industrial applications.




Ali Kaveh was born in 1948 in Tabriz, Iran. After graduation from the Department of Civil Engineering at the University of Tabriz in 1969, he continued his studies on Structures at Imperial College of Science and Technology at London University, and received his M.S., DIC and Ph.D. Degrees in 1970 and 1974, respectively. He then joined the Iran University of Science and Technology in Tehran where he is presently Professor of Structural Engineering. Professor Kaveh is the author of 275 papers published in international journals and 130 papers presented at international conferences. He has authored 23 books in Farsi and 4 books in English published by Wiley, the American Mechanical Society, Research Studies Press and Springer Verlag. He is the author/inventor of several metaheuristic algorithms. His works on these algorithms are mainly focused on applications on structural design problems. The title of his presentation at the workshop will be  "Optimal Analysis for Optimal Design of Structures".


Patrick SIARRY 


Patrick Siarry is an engineer graduated from Ecole Supérieure d’Electricité (Supélec, France) in 1977. He then received the PhD degree from the University Paris 6, in 1986 and the Doctorate of Sciences (Habilitation) from the University Paris 11, in 1994. He was first involved in the development of analog and digital models of nuclear power plants at Electricité de France (E.D.F.). Since 1995 he is a professor in automatics and operations research at the University Paris-Est Créteil (UPEC), France. He is head of the team “Signal and Image Processing” of the “Signals, Images & Intelligent Systems” laboratory of UPEC. His main research interests are the development of methods for solving “hard” optimization problems occurring in real-life engineering design projects. He is particularly interested in “metaheuristic” approaches, such as simulated annealing, evolutionary algorithms, ant colonies, and particle swarms. His main contributions are related to the adaptation of discrete metaheuristics for solving continuous optimization problems. The methods developed in the team have been applied in various fields: image processing, computer-aided design of electronic circuits, fitting of process models to experimental data, learning of fuzzy rule bases and neural networks, etc.

"In this tutorial, we firstly present the general frame of "difficult" continuous optimization: after a short description of a few typical applications, we point out the difficulties peculiar to continuous problems. Then we describe some pitfalls of adapting metaheuristics to continuous variable problems. In a second part, we present, as an illustration, the methods that we have proposed to adapt some metaheuristics: simulated annealing, tabu search, genetic algorithms and ant colony algorithms. We outline some perspectives or works in progress, particularly dealing with particle swarm optimization. Lastly, we show, as an example, an application in the field of biomedical engineering of a continuous ant colony algorithm: the registration of retinal angiograms."


Xin-She Yang


   ​Xin-She Yang is Reader in Modelling and Optimization at Middlesex University (UK) and Adjunct Professor at Reykjavik  University (Iceland). After obtained his DPhil in Applied Mathematics from Oxford University, he worked at Cambridge University  and then at National Physical Laboratory as a Senior Research Scientist. He is the Editor-in-Chief of the International Journal of  Mathematical Modelling and Numerical Optimisation (IJMMNO) and Director of International Consortium for Optimization and Modelling in Science and Industry (iCOMSI). He is also the IEEE CIS Task Force Chair on Business Intelligence and  Knowledge Management. As the main developer of three metaheuristic algorithms (bat algorithm, cuckoo search, firefly  algorithm), his research interests include metaheuristics, engineering design, modelling and simulation. He has    authored/edited 15 books and published more than 200 papers. His talk will be about "Nature-Inspired Metaheuristics:  Success and Challenges".



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