Genetic Algorithms are an effective way to solve optimisation problems. If the fitness test takes a long time to perform then the Genetic Algorithm may take a long time to execute. Using conventional fitness functions Approximately a third of the time may be spent testing individuals that have already been tested. Intelligent Fitness Functions can be applied to improve the efficiency of the Gen...

in this paper, a new genetic algorithm (ga) is presented for solving the multi-mode resource-constrained project scheduling problem (mrcpsp) with minimization of project makespan as the objective subject to resource and precedence constraints. a random key and the related mode list (ml) representation scheme are used as encoding schemes and the multi-mode serial schedule generation scheme (mssg...

Apparent shear stress acting on a vertical interface between the main channel and floodplain in a compound channel serves to quantify the momentum transfer between sub sections of this cross section. In this study, three soft computing methods are used to simulate apparent shear stress in prismatic compound channels. The Genetic Algorithm Artificial neural network (GAA), Genetic Programming (GP...

This paper describes the innovative use of genetic programming (GP) to solve the grasp synthesis problem for multifingered robot hands. The goal of our algorithm is to select a ÒbestÓ grasp of an object, given some information about the object geometry and some userdefined Òfitness functionsÓ which intuitively delineate ÒgoodÓ from ÒbadÓ grasp qualities. The fitness functions are used by the sp...

This thesis introduces Intelligent Fitness Functions and Partial Fitness Functions both of which can improve the performance of a genetic algorithm which is limited to a fixed run time. An Intelligent Fitness Function is defined as a fitness function with a memory. The memory is used to store information about individuals so that duplicate individuals do not need to have their fitness tested. D...

This paper describes the innovative use of a genetic algorithm to solve the grasp synthesis problem for multifingered robot hands. The goal of our algorithm is to select a ‘best’ grasp of an object, given some information about the object geometry and some userdefined ‘fitness functions’ which intuitively delineate ‘good’ from ‘bad’ grasp qualities. The fitness functions are used by the special...

This paper presents the VHDL implementation of fault tolerant cellular genetic algorithm. The goal of paper is to harden the hardware implementation of the cGA against single error upset (SEU), when affecting the fitness registers in the target hardware. The proposed approach, consists of two phases; Error monitoring and error recovery. Using innovative connectivity between processing elements ...

One of sheet severe plastic deformation (SPD) operation, namely constrained groove pressing (CGP), is investigated here in order to specify the optimum values for geometrical variables of this process on pure aluminium sheets. With this regard, two different objective functions, i.e. the uniformity in the effective strain distribution and the necessary force per unit weight of the specimen, are...