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EU/ME - the metaheuristics community

2nd Mini EURO Conference on Variable Neighborhood Search MEC-VNS 2012

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The 2nd Mini EURO Conference dedicated to Variable Neighborhood Search (MEC-VNS) will be held in Herceg Novi (Montenegro) October 4-7, 2012.

The Mini EURO Conferences (MEC) constitute one of the instruments provided by EURO (the Association of European Operational Research societies) to promote the research in its field of interest. Each MEC is an specialized conference focusing a particular promising OR theme of research. These events are organized to allow specialists and practitioners of the selected topic of research to effectively screen papers participate in lively debates.

VNS is a metaheuristic based on systematic changes in the neighbour-rhood structure within a search, for solving optimization problems and related tasks. The main goal of the 2nd MEC-VNS is to provide a stimulating environment in which researchers coming from various scientific fields can share and discuss their knowledge, expertise and ideas related to the VNS Metaheuristic and its applications.


Happy new year 2012!

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Dear EU/MEmbers,

As usual in this period, this is time to wish you the best for 2012. May this year be the best for you, your family and your co-workers.



The EU/ME coordinators.

Last Updated on Wednesday, 11 January 2012 07:27

Transportation Research Part B: Methodological, 46(1), 2012

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Efficient Transit Schedule Design of timing points: A comparison of Ant Colony and Genetic Algorithms

by Ehsan Mazloumi, Mahmoud Mesbah, Avi Ceder, Sara Moridpour and Graham Currie

AbstractThis work defines Transit Schedule Design (TSD) as an optimization problem to construct the transit schedule with the decision variables of the location of timing points and the amount of slack time associated with each timing point. Two heuristic procedures, Ant Colony and Genetic Algorithms, are developed for constructing optimal schedules for a fixed bus route. The paper presents a comparison of the fundamental features of the two algorithms. They are then calibrated based on data generated from micro-simulation of a bus route in Melbourne, Australia, to give rise to (near) optimal schedule designs. The algorithms are compared in terms of their accuracy and efficiency in providing the minimum cost solution. Although both procedures prove the ability to find the optimal solution, the Ant Colony procedure demonstrates a higher efficiency by evaluating less schedule designs to arrive at a ‘good’ solution. Potential benefits of the developed algorithms in bus route planning are also discussed.


Doctoral Course in "Local Distribution Planning"

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Molde University College, Specialized University in Logistics, are arranging a doctoral course in Local Distribution Planning. This will take place in Molde, Norway, 5-12 march 2012.

The presenters will be

  • Professor Michel Gendreau CIRRELT, Canada
  • Professor Teodor Crainic CIRRELT, Canada
  • Associate Professor Lars Magnus Hvattum NTNU, Norway
  •  Associate Professor Johan Oppen Molde Univ. College, Norway
  • Chief Research Scientist Geir Hasle SINTEF, Norway  
For scope, course details, etc., see Please also note that the course is sponsored with two student grants from EU/ME, see the course web for details.
Last Updated on Wednesday, 01 February 2012 09:55

Journal of Heuristics 17(6), 2011

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A comparative study of crossover in differential evolution

by Chuan Lin, Anyong Qing and Quanyuan Feng

Abstract: In order to understand the role of crossover in differential evolution, theoretical analysis and comparative study of crossover in differential evolution are presented in this paper. Two new crossover methods, namely consecutive binomial crossover and non-consecutive exponential crossover, are designed. The probability distribution and expectation of crossover length for binomial and exponential crossover used in this paper are derived. Various differential evolution algorithms with different crossover methods including mutation-only differential evolution are comprehensively compared at system level instead of parameter level. Based on the theoretical analysis and simulation results, the effect of crossover on the reliability and efficiency of differential evolution algorithms is discussed. Some insights are revealed.

Last Updated on Tuesday, 22 November 2011 10:13

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