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
* Christos D. Tarantilis,
* Diomidis D. Spinellis,
* Michel Gendreau,
Université de Montréal
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://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.