To solve a problem using Genetic Algorithms (GAs), a solution must be encoded into a binary string. The length of the binary string represents the size of the problem. As the length of the binary string increases, the size of the search space also increases at an exponential rate. To reduce the search space, one approach is to use a compressed encoding chromosome. This paper presents a genetic ...

The BBN scheduling group contracts with both government and industry to perform research and development for geneticalgorithm-based scheduling. We have developed custom real-world automated scheduling systems for different clients. Here, I relate some of the insight gained from our experience organized into a few broad categories. 1 SELLING THE PROJECT Clearly, one of the critical parts of buil...

This paper is a continuation of two previous papers where the authors used Genetic Algorithm with automated problem decomposition strategy for small scale capacitated vehicle routing problems (CVRP) and vehicle routing problem with time windows (VRPTW). In this paper they have extended their scheme to large scale capacitated vehicle routing problems by introducing selective search version of th...

Alliot et al. [1] who used GAs for solving conflicts in air traffic control. Davis [2] and Giffer [3] applied genetic algorithms to problems involving job shop and production scheduling, respectively. These, along with countless other researchers have found GAs to be a valuable tool in problem solving and optimization environments.Although the high strength-to-weight properties of composite mat...

1. Background Because of its negative effects on health and living conditions, air pollution has long emerged as one of the most acute problems in many metropolitan areas. A major source of this pollution is the emissions from vehicular traffic (see e.g., Cai et al., 2009; Sharma et al., 2010; Environmental Protection Agency, 2011). They contribute considerably to the level of, e.g., carbon mon...