A novel early stage drip irrigation system cost estimation model based on management and environmental variables by Masoud Pourgholam-Amiji, Khaled Ahmadaali, Abdolmajid Liaghat

“…Then, different machine learning models such as Multivariate Linear Regression, Support Vector Regression, Artificial Neural Networks, Gene Expression Programming, Genetic Algorithms, Deep Learning, and Decision Trees, were used to estimate the costs of each of the of the aforementioned sections. …”
Get full text

Spare Parts Inventory Optimization for Military Vehicles Using a Mixed Probability Distribution by Mojtaba Salehi, Mojtaba Omidvar, Shohreh Shariati

“…The meta-heuristic method based on the genetic algorithm has been applied to save the total costs. …”
Get full text

Improved FGA and Its Applications in the Optimal Design of Four Bar Mechanism by Ye Bin, Luo Jinliang

“…The genetic algorithm can effectively handle some complex optimal problems that the conventional optimization methods can’t solve. …”
Get full text

Load Balancing Selection Method and Simulation in Network Communication Based on AHP-DS Heterogeneous Network Selection Algorithm by Weiwei Xiao

“…This article proposes an Analytic Hierarchy Process Dempster-Shafer (AHP-DS) and similarity-based network selection algorithm for the scenario of dynamic changes in user requirements and network environment; combines machine learning with network selection and proposes a decision tree-based network selection algorithm; combines multiattribute decision-making and genetic algorithm to propose a weighted Gray Relation Analysis (GRA) and genetic algorithm-based network access decision algorithm. …”
Get full text

Fault Tolerant PLBGSA: Precedence Level Based Genetic Scheduling Algorithm for P2P Grid by Piyush Chauhan, Nitin

“…Benefit of a genetic algorithm is that it takes into consideration multiple criteria while scheduling. …”
Get full text

Design and Optimization of E-Commerce Logistics Distribution System Based on Multiobjective Function by Hui Wen

“…To reduce the complexity and multiple constraints of logistics distribution routing problems, the author proposes an improved genetic algorithm, adaptive immune genetic algorithm (AIGA). …”
Get full text

Optimasi Fuzzy C-Means dan K-Means Menggunakan Algoritma Genetika untuk Pengklasteran Dataset Diabetic Retinopathy by Muhammad Ezar Al Rivan, Steven Steven, William Tanzil

“…Based on the comparison of Genetic Algorithm  Fuzzy C-Means and Genetic Algorithm K-Means iterations, it can be concluded that Genetic Algorithm Fuzzy C-Means has a better number of iteration than Genetic Algorithm K-Means. …”
Get full text

Fuzzy Mixed Assembly Line Sequencing and Scheduling Optimization Model Using Multiobjective Dynamic Fuzzy GA by Farzad Tahriri, Siti Zawiah Md Dawal, Zahari Taha

“…Trapezoidal fuzzy numbers are implemented for variables such as operation and travelling time in order to generate results with higher accuracy and representative of real-case data. An improved genetic algorithm called fuzzy adaptive genetic algorithm (FAGA) is proposed in order to solve this optimization model. …”
Get full text

Metaheuristic Algorithm for Solving Biobjective Possibility Planning Model of Location-Allocation in Disaster Relief Logistics by Farnaz Barzinpour, Mohsen Saffarian, Ahmad Makoui, Ebrahim Teimoury

“…The results of genetic algorithm are compared with the results provided by simulated annealing algorithm and LINGO software. …”
Get full text

Multiobjective Multidepot Capacitated Arc Routing Optimization Based on Hybrid Algorithm by Liang Wu

“…The multidepot capacitated arc routing problem (CARP) is investigated with the hybrid optimization algorithm of the Dijkstra algorithm and genetic algorithm. The complex multidepot CARP is transformed into multiple single depot CARP by systematic clustering analysis. …”
Get full text

Optimal Scheduling for Retrieval Jobs in Double-Deep AS/RS by Evolutionary Algorithms by Kuo-Yang Wu, Sendren Sheng-Dong Xu, Tzong-Chen Wu

“…Three types of evolutionary algorithms, the Genetic Algorithm (GA), the Immune Genetic Algorithm (IGA), and the Particle Swarm Optimization (PSO) algorithm, are implemented to obtain the optimal assignments. …”
Get full text

Empirical Study of Multi-Objective Risk Portfolio Optimization Based on NSGA-II by Qian Gao, Aleš Kresta

“…This study aims to uncover the potential advantages of dynamic portfolio optimization using a multi-objective genetic algorithm to address the challenges of ever-changing market conditions. …”
Get full text

Optimization on Production-Inventory Problem with Multistage and Varying Demand by Duan Gang, Chen Li, Li Yin-Zhen, Song Jie-Yan, Akhtar Tanweer

“…A nonlinear hybrid integer constrained optimization is modeled to minimize the total cost including setup cost and holding cost in the planning horizon. A genetic algorithm is developed for the problem. A series of computational experiments with different sizes is used to demonstrate the efficiency and universality of the genetic algorithm in terms of the running time and solution quality. …”
Get full text

Disordered and Multiple Destinations Path Planning Methods for Mobile Robot in Dynamic Environment by Yong-feng Dong, Hong-mei Xia, Yan-cong Zhou

“…A sinusoidal adaptive genetic algorithm is adopted. It can calculate the crossover probability and mutation probability adaptively changing with environment at any time. …”
Get full text

Optimization of Port Emergency Materials Dispatch with Time Windows Constraints under Uncertainties by Bowei Xu, Yuqing Wang, Junjun Li

“…Through numerical experiments, the algorithm proposed in this study was compared with the genetic algorithm and adaptive genetic algorithm. The experimental results show that the model and algorithm proposed in this study can effectively reduce the total cost of containers in a terminal while ensuring the priority dispatch of emergency materials, reducing the overlapping part of the time window, optimizing the arrival mode of external trucks, and reducing the waiting time of external trucks, effectively alleviating the terminal congestion problem.…”
Get full text

An improved optimization algorithm in cross-layer allocation for multi-user OFDM system by Yaqin PAN, Li ZHANG, Shibing ZHANG

“…A cross-layer resource allocation model in multiuser OFDM system was proposed，which combined the channel state in physical layer and the user’s queue in MAC layer.The proposed hybrid optimization algorithm made use of the advantages of genetic algorithm and tabu search algorithm to improve the crossover of genetic algorithm.It would improve the global search ability，converge to the global optimal value faster，solve the cross-layer resource allocation problem more effectively and meet the user’s quality of service better.The simulation results show that the improved hybrid algorithm increases the throughput，reduces the average delay and improves the QoS of the system.…”
Get full text

A Dynamic Task Scheduling Algorithm for Airborne Device Clouds by Bao Deng, Zhengjun Zhai

“…The task scheduling model based on genetic algorithm and random scheduling algorithm is compared through comparison experiments, which show that the assignment time of the task scheduling model based on genetic algorithm is shortened by 11.82% to 48.51% and the energy consumption is reduced by 22.28% to 47.52% under different load conditions.…”
Get full text

A Low-Complexity GA-WSF Algorithm for Narrow-Band DOA Estimation by Haihua Chen, Jialiang Hu, Hui Tian, Shibao Li, Jianhang Liu, Masakiyo Suzuki

“…This paper proposes a low-complexity estimation algorithm for weighted subspace fitting (WSF) based on the Genetic Algorithm (GA) in the problem of narrow-band direction-of-arrival (DOA) finding. …”
Get full text

Memetic-based schedule synthesis for communication on time-triggered embedded systems by Heyuan Shi, Kun Tang, Chengbao Liu, Xiaoyu Song, Chao Hu, Jiaguang Sun

“…Memetic-based schedule synthesis algorithm is based on memetic algorithm, which incorporates local search in the iterations of general genetic algorithm. We compare memetic-based schedule synthesis algorithm with genetic algorithm in different scale of time-triggered network-on-chip and number of messages. …”
Get full text

Spectral optimization of supercontinuum shaping using metaheuristic algorithms, a comparative study by Mathilde Hary, Teemu Koivisto, Sara Lukasik, John M. Dudley, Goëry Genty

“…We find that the genetic algorithm and particle swarm optimizer are more robust and perform better, with the particle swarm optimizer converging faster. …”
Get full text