This paper addresses the problem of simultaneous localization and mapping (SLAM) by a mobile robot. The SLAM problem is defined as a global optimization problem in which the objective is to search the space of possible robot maps. A genetic algorithm is described for solving this problem, in which a population of candidate solutions is progressively refined in order to find a globally optimal s...

The Complete Coverage Path Planning (CCPP) is a key technology in the field of agricultural robots, and has great significance for improving efficiency quality tillage, fertilization, harvesting, other robot operations, as well reducing operation energy consumption. traditional boustrophedon- or heuristic-search-algorithm-based CCPP methods, when coping with irregular boundaries, obstacles, com...

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...

In this paper we glance through the various approaches used by the researchers to develop an automatic timetable using Genetic algorithms. The optimized genetic algorithm can be used with the heuristic approach to design and develop the timetable of an institute. At stake during the process of development, the stakeholders are the professors and the students. The efficient utilization of the in...

This paper exemplifies a framework for development of multi-objective genetic algorithm based job sequencing method by taking account of multiple resource constraints. Along this, Theory of Constraints based Drum-Buffer-Rope methodology has been combined with genetic algorithm to exploit the system constraints. This paper introduces the Drum-Buffer-Rope to exploit the system constraints, which ...

Surrogate models of fitness have been presented as a way of reducing the number of fitness evaluations required by evolutionary algorithms. This is of particular interest with expensive fitness functions where the time taken for building the model is outweighed by the saving of using fewer function evaluations. In this paper, we show how a Markov network model can be used as a surrogate fitness...

Do nasopharyngeal carcinoma (NPC) patients benefit from induction chemotherapy (IC)? This problem is of great clinical interest; however, it difficult to obtain an accurate and interpretable model inform IC decisions for NPC patients. In this study, a time-to-event supervised genetic algorithm was developed decision-making algorithm, the fitness function directly related time-to-event, which re...

This paper describes an application of fuzzy-logic and evolutionary computation to the optimization of the start-up phase of a combined cycle power plant. We modelled process experts’ knowledge with fuzzy sets over the process variables in order to get the needed cost function for the Genetic Algorithm (GA) we used to obtain the optimal regulations. Due to the obvious impossibility to test the ...

Operation of reservoirs, often for conflicting purposes, is a difficult task. The uncertainty associated with reservoir operations is further increased due to the on-going hydrological impacts of climate change. Therefore, various artificial intelligence techniques such as genetic algorithms, ant-colony optimization, fuzzy logic and mathematical optimization methods such as Linear programming, ...