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Last Call for Papers (EXTENDED DEADLINE) IEEE Intelligent Systems Special Issue on “Advanced Heuristics in Transportation and Logistics” Submissions due 18 February 2005 In today’s transportation and logistics environment, industries are calling for immediate action on developing computational and simulation-based methods that will lead to faster transactions, reduced operating costs, and improved performance and customer service. They also want these methods to help provide more control and flexibility in their operations such as production and location planning, warehousing, distribution, and transportation. Transportation and logistics organizations often face large-scale combinatorial problems on both operational and strategic levels. In such problems, all possible combinations of decisions and variables must be examined to find a solution; consequently, no partial enumeration-based exact algorithm can consistently solve them. This occurs because sharp lower bounds on the objective value are hard to derive, thus causing a slow convergence rate. By exploiting problem-specific characteristics, classical heuristic methods aim at a relatively limited exploration of the search space, thereby producing acceptable-quality solutions in modest computing times. As a major departure from a classical heuristic, a metaheuristic method implies a higher-level strategy controlling a lower-level heuristic method. Metaheuristics exploit not only the problem characteristics but also ideas based on artificial intelligence rationale, such as different types of memory structures and learning mechanisms, as well as the analogy with other optimization methods found in nature. Solutions produced by metaheuristics typically are of much higher quality than those obtained with classical heuristic approaches. Evidently, metaheuristic approaches’ success arises from intelligent exploitation of the problem structure and a good deal of insight achieved by the effective interplay between intensification (concentrating the search into a specific region of the search space) and diversification (elaborating various diverse regions in the solution space) mechanisms. This special issue (http://www.computer.org/intelligent/cfp15.htm) of IEEE Intelligent Systems will feature original, high-quality submissions that address all aspects of metaheuristic methods as applied to transportation and logistics. Applications-oriented papers will be extremely welcome, as well as papers addressing computational performance of metaheuristic methods on well-known benchmark instances. The methods of interest include, but are not limited to, * Tabu search * Annealing-based algorithms * Evolutionary algorithms * Adaptive memory procedures * GRASP (greedy randomized adaptive search procedures) * Ant systems * Neural networks * Variable neighbourhood search * Guided local search * Scatter search and Path relinking * Simulation-based algorithms Special Issue Guest Editors * Christos D. Tarantilis, Athens University of Economics & Business * Diomidis D. Spinellis, Athens University of Economics & Business * Michel Gendreau, Université de Montréal Important Dates * Submission deadline: 18 February * Initial decision letter sent: 11 March * Final decision: 4 April Submission Guidelines Submissions should be 3,000 to 7,500 words (counting a standard figure or table as 200 words) and should follow the magazine’s style and presentation guidelines (see <http://www.computer.org/intelligent/author.htm> http://computer.org/intelligent/author.htm). References should be limited to 10 citations. To submit a manuscript for peer-reviewed consideration, please access the IEEE Computer Society Web-based system, Manuscript Central, at <http://cs-ieee.manuscriptcentral.com/index.html> http://cs-ieee.manuscriptcentral.com/index.html.