The paper has demonstrated InSAR phase unwrapping using Hybrid Genetic Algorithm (GHA). The three dimensional phase unwrapping is performed using three-dimensional best-path avoiding singularity loops (3DBPASL) algorithm. Then phase matching is implemented with 3DBPASL using Hybrid Genetic Algorithm (GHA). Further, the combination between GHA and 3DBPASL is used to eliminate the phase decorrela...

This study developed a novel model, HGA-SVR, for type of kernel function and kernel parameter value optimization in support vector regression (SVR), which is then applied to forecast the maximum electrical daily load. A novel hybrid genetic algorithm (HGA) was adapted to search for the optimal type of kernel function and kernel parameter values of SVR to increase the accuracy of SVR. The propos...

This paper deals with the one-dimensional Bin Packing Problem (1-D BPP). Exact solution methods can only be used for very small instances, hence for real-world problems we have to focus on heuristic methods. In recent years, researchers have started to apply evolutionary approaches to this problem, including Genetic Algorithms and Evolutionary Programming. In this paper, we propose a Hybrid Gen...

In this research, a new hybrid model for the redundancy allocation problem (RAP) in series-parallel configuration with k-out-of-n subsystem is presented. given model, policy set to an active, warm standby, or no redundancy. standby policy, imperfect switch detected component's failure and replaced fail component one. So, subsystems' one of model's decision variables. We presented objective func...

In this paper, an efficient hybrid genetic algorithm (HGA) and its variants for the wellknown combinatorial optimization problem, the quadratic assignment problem (QAP) are discussed. In particular, we tested our algorithms on a special type of QAPs, the structured quadratic assignment problems. The results from the computational experiments on this class of problems demonstrate that HGAs allow...

This paper considers a problem in which orders are processed by either one of two parallel machines and delivered by a single delivery truck to one customer area. Coordination among production stage and distribution stage in the supply chain to achieve ideal overall system performance has become more practical and has received a lot of attention from both industry practitioners and academic res...

In this paper, a hybrid intelligent parameter estimation algorithm is proposed for predicting the strip temperature during laminar cooling process. The algorithm combines a hybrid genetic algorithm (HGA) with grey case-based reasoning (GCBR) in order to improve the precision of the strip temperature prediction. In this context, the hybrid genetic algorithm is formed by combining the genetic alg...

evolutionary algorithms are some of the most crucial random approaches tosolve the problems, but sometimes generate low quality solutions. on the otherhand, learning automata are adaptive decision-making devices, operating onunknown random environments, so it seems that if evolutionary and learningautomaton based algorithms are operated simultaneously, the quality of results willincrease sharpl...

This paper addresses two NP-hard and strongly related problems in production planning of flexible manufacturing system (FMS), part type selection problem and machine loading problem. Various flexibilities such as alternative machines, tools, and production plans are considered. Real coded genetic algorithms (RCGA) that uses an array of real numbers as chromosome representation is developed to h...

In this paper, the problem of lot sizing, scheduling and delivery of several items in a twostage supply chain over a finite planning horizon is studied. Single supplier via a flexible flow line production system (FFL), produces several items and delivers them directly to an assembly facility. Based on basic period (BP) strategy, a new mixed zero-one nonlinear programming model has been develope...