Resumen
The article focuses on global perceptions of journals publishing e-commerce research. E-commerce encompasses all aspects of business and market processes enabled by Internet and Web technologies. E-commerce, like information systems, is interdisciplinary in nature, borrowing concepts and theories from computer science, psychology, economics, organizational theory and the natural sciences, as well as from applied areas of study such as marketing, management, finance, accounting, engineering and law. Research findings in e-commerce can be disseminated to scientists and practitioners in the form of journal articles. But the interdisciplinary nature of e-commerce often makes it difficult to match the research being performed with the journals that currently exist in established disciplines and fields of study. While e-commerce articles are accepted in these traditional outlets, it can be a difficult process if they are perceived to be outside the scope of journals. In an attempt to address this problem, multidisciplinary journals aimed specifically at e-commerce research have begun appearing over the last several years. In academia, researchers strive to have their research published in top-quality journals, usually in those in which articles are refereed to the highest standards and have an excellent editorial board.

Resumen
The article reveals that even with ever-increasing computing power as of August 1, 2002, there are still many types of problems that are very difficult to solve. Particularly, combinatorial optimization problems continue to pose challenges to scientists. An example of this type of problem can be found in product design. Genetic algorithms use biological methods such as reproduction, crossover and mutation to quickly search for solutions to complex problems. More recently, scientists have been turning to insects for ideas that can be used for heuristics. In this context, it is asserted that following a trail of insects as they work together to accomplish a task offers unique possibilities for problem solving. Many aspects of the collective activities of social insects such as ants are self-organizing meaning that complex group behavior emerges from interactions of individuals who exhibit simple behaviors by themselves. Ant colony optimization is a meta-heuristic that uses artificial ants to find good solutions to difficult combinatorial optimization problems.