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The current research aims to identify new combined genetic algorithm methods to solve complex problems. The researcher has analyzed the results and findings of the previous researchers using a systematic reviewing approach and has identified the effective factors by implementing the 7 steps of Sandelowski and Barroso’s method. Among 4320 articles, 54 articles were selected based on the CASP method. In this manner, in order to evaluate reliability and quality control, the Kappa index was used, and its value was deemed to be in high compatibility regarding the identified factors. The results of the analysis of the collected data in ATLAS TI software led to the identification of 9 categories and 33 primary codes of new combined genetic algorithm methods to solve complex problems. Based on the coding, 9 categories, and 33 initial codes were identified. The identified categories are layout design, supply network, programming, Anticipation, inventory control, information security, imaging, medical imaging and wireless network. [ABSTRACT FROM AUTHOR]

The modelling of a biomass fluidized bed gasification system, one of the most effective ways to produce energy from biomass resources and wastes, has been performed in this study. The effect of the turbulence phenomena, including calculations relating to flow turbulence, chemical fuel reactions, and energy and momentum exchange between multiple solid and gas phases, has been taken into account in the current research as a novel approach. A computational fluid dynamics case study model that combines equations with comprehensive geometry has been considered. Results have been compared with published operational records of an existing power plant to validate the model. The solid particle distribution, the velocity of the mixture and gas phase, the turbulent flow viscosity ratio, and the temperature distribution in the model indicated the accuracy of the simulation performance compared with the experimental studies. The production of the molar fraction of the constituent elements of the synthesis gas has been evaluated in transient conditions. Additionally, 35 s after the process began, the system's performance was estimated, and the results indicated the average molecular weights of hydrogen, carbon monoxide, carbon dioxide, and methane are 26%, 23%, 12.5%, and 3.3%, respectively, which presented high precision with the experimental results. [ABSTRACT FROM AUTHOR]

The hub location problems involve locating facilities and designing hub networks to minimize the total cost of transportation (as a function of distance) between hubs, establishing facilities and demand management. In this paper, we consider the capacitated cluster hub location problem because of its wide range of applications in real-world cases, especially in transportation and telecommunication networks. In this regard, a mathematical model is presented to address this problem under capacity constraints imposed on hubs and transportation lines. Then, a new hybrid algorithm based on simulated annealing and ant colony optimization is proposed to solve the presented problem. Finally, the computational experiments demonstrate that the proposed heuristic algorithm is both effective and efficient. [ABSTRACT FROM PUBLISHER]

This paper considers the multi-depot vehicle routing problem with time window in which each vehicle starts from a depot and there is no need to return to its primary depot after serving customers. The mathematical model which is developed by a new approach aims to minimize the transportation costs including the travelled distance, the latest and the earliest arrival time penalties. Furthermore, in order to reduce the problem searching space, a novel GA clustering method is developed. Finally, Experiments are run on a number of problems with varying depots and time window and customer sizes. The method is compared to two other clustering techniques, fuzzy C means (FCM) and K-means algorithms. Experimental results show the robustness and effectiveness of the proposed algorithm. [ABSTRACT FROM AUTHOR]

A genetic algorithm is a metaheuristic proposed to derive approximate solutions for computationally hard problems. In the literature, several successful applications have been reported for graph-based optimization problems, such as scheduling problems. This paper provides one definition of periodic vehicle routing problem for single and multidepots conforming to a wide range of real-world problems and also develops a novel hybrid genetic algorithm to solve it. The proposed hybrid genetic algorithm applies a modified approach to generate a population of initial chromosomes and also uses an improved heuristic called the iterated swap procedure to improve the initial solutions. Moreover, during the implementation a hybrid algorithm, cyclic transfers, an effective class of neighborhood search is applied. The author uses three genetic operators to produce good new offspring. The objective function consists of two terms: total traveled distance at each depot and total waiting time of all customers to take service. Distances are assumed Euclidean or straight line. These conditions are exactly consistent with the real-world situations and have received little attention in the literature. Finally, the experimental results have revealed that the proposed hybrid method can be competitive with the best existing methods as asynchronous parallel heuristic and variable neighborhood search in terms of solution quality to solve the vehicle routing problem. [ABSTRACT FROM AUTHOR]

In this research, a Markov analysis of acceptance sampling plans in a single stage and in two stages is proposed, based on the quality of the items inspected. In a stage of this policy, if the number of defective items in a sample of inspected items is more than the upper threshold, the batch is rejected. However, the batch is accepted if the number of defective items is less than the lower threshold. Nonetheless, when the number of defective items falls between the upper and lower thresholds, the decision-making process continues to inspect the items and collect further samples. The primary objective is to determine the optimal values of the upper and lower thresholds using a Markov process to minimise the total cost associated with a batch acceptance policy. A solution method is presented, along with a numerical demonstration of the application of the proposed methodology. [ABSTRACT FROM AUTHOR]