In modern manufacturing systems like multi-resource constrained project scheduling problem with the multiple modes (mcPSP-mM) is complicated because of the complex interrelationships between the units of the different stages. In this paper, we develop an adaptive genetic algorithm (aGA) to solve the mcPSP-mM which is a well known NP-hard problem. A new aGA algorithm approach for solving these m...

The performance of Genetic Algorithm (GA) depends on various operators. Crossover operator is one of them. Crossover operators are mainly classified as application dependent crossover operators and application independent crossover operators. Effect of crossover operators in GA is application as well as encoding dependent. This paper will help researchers in selecting appropriate crossover oper...

AGDISP (Aerial Spray Simulation Model) is used to predict the deposition of spray material released from an aircraft. Determining the optimal input values to AGDISP in order to produce a desired spray material deposition is extremely difficult (NP hard). SAGA, an intelligent optimization method based on the simple genetic algorithm, was developed to solve this problem. In this paper, we apply s...

in this paper, the maximal dissipative extensions of a symmetric singular 1d discrete hamiltonian operator with maximal deficiency indices (2,2) (in limit-circle cases at ±∞) and acting in the hilbert space ℓ_{ω}²(z;c²) (z:={0,±1,±2,...}) are considered. we consider two classes dissipative operators with separated boundary conditions both at -∞ and ∞. for each of these cases we establish a self...

This paper proposes a new approach based on Bonferroni mean operator and possibility degree to solve fuzzy multi-attribute decision making (FMADM) problems in which the attribute value takes the form of interval type-2 fuzzy numbers. We introduce the concepts of interval possibility mean value and present a new method for calculating the possibility degree of two interval trapezoidal type-2 fuz...

In this paper, we propose a hybrid genetic algorithm based on variable grouping and uniform design for global optimization problems, a function formula based grouping (FBG) strategy is adopted to classify the separable variables into different groups and put the interactive variables into the same group. In this way, the problem considered can be changed into several lower dimension sub-problem...

In this paper, we consider the role of the crossover operator in genetic algorithms. Specifically, we study optimisation problems that exhibit many local optima and consider how crossover affects the rate at which the population breaks the symmetry of the problem. As an example of such a problem, we consider the subset sum problem. In doing so, we demonstrate a previously unobserved phenomenon,...

In this paper, we propose a novel hybrid genetic algorithm (GA) that finds a globally optimal partition of a given data into a specified number of clusters. GA's used earlier in clustering employ either an expensive crossover operator to generate valid child chromosomes from parent chromosomes or a costly fitness function or both. To circumvent these expensive operations, we hybridize GA with a...

In order to solve the problem of flexible job-shop scheduling, this paper proposed a novel quantum genetic algorithm based on cloud model. Firstly, a simulation model was established aiming at minimizing the completion time, the penalty and the total cost. Secondly, the method of double chains structure coding including machine allocation chain and process chain was proposed. The crossover oper...

Crossover operator is the predominant operator in most of Genetic Programming (GP) system. The empirical evidence shows that along with building blocks are constructed bigger and bigger as GP evolution proceeds, the crossover operator tends to disrupt those building blocks rather than preserve them. The traditional GP crossover primarily acts as macromutation. Looseness is used for representing...