OBJECTIVES The presence of microcalcifications (MCs), clusters of tiny calcium deposits that appear as small bright spots in a mammogram, has been considered as a very important indicator for breast cancer diagnosis. Much research has been performed for developing computer-aided systems for the accurate identification of MCs, however, the computer-based automatic detection of MCs has been shown...

This paper describes a hybrid genetic algorithm for solving instances of the Fixed Channel Assignment Problem (FCAP), a problem that is frequently encountered by designers of mobile telecommunication networks. The hybrid GA manipulates solutions which model networks directly, allowing it to provide realistic assignments for highly constrained problems. Unfortunately, such solutions can be very ...

We propose a powerful Reinforced Hybrid Genetic Algorithm (RHGA) for the famous NP-hard Traveling Salesman Problem (TSP). RHGA combines reinforcement learning technique with well-known Edge Assembly Crossover genetic algorithm (EAX-GA) and Lin-Kernighan-Helsgaun (LKH) local search heuristic. With help of proposed hybrid mechanism, evolution EAX-GA LKH can boost each other's performance. And bas...

This paper studies Genetic Programming (GP) and its relation to the Genetic Algorithm (GA). GP uses a GA approach to breed successive populations of programs, represented in the chromosomes as parse trees, until a program that solves the problem emerges. However, parse trees are not naturally homologous, consequently changes had to be introduced into GP. To better understand these changes it wo...

The parts optimization are very important for scroll compressor design. According to existing problems of current optimization algorithm and actual optimization problems, the improved optimization algorithm—genetic-particle swarm optimization (GA-PSO) is proposed for scroll plate optimization. The optimization method integrates crossover of genetic algorithm (GA) and evolutionary mechanism of p...

multi-criteria shortest path problems (mspp) are called as np-hard. for mspps, a unique solution for optimizing all the criteria simultaneously will rarely exist in reality. algorithmic and approximation schemes are available to solve these problems; however, the complexity of these approaches often prohibits their implementation on real-world applications. this paper describes the development ...

In actual complicated optimization problems, it is often difficult to find a global optimum solution in admissible computing time. Therefore, in industrial problems, we should find quasi-optimum solution in admissible computing time. In that case, evolutionary computations (ECs) are very attractive. There are several algorithms in the EC family; genetic algorithm (GA), evolutionary strategy (ES...