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Journal articles on the topic 'Hybrid ga-vns'

Author: Grafiati

Published: 4 June 2025

Last updated: 1 August 2025

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1

Fauziyah, Aprilia Nur, and Wayan Firdaus Mahmudy. "Hybrid Genetic Algorithm for Optimization of Food Composition on Hypertensive Patient." International Journal of Electrical and Computer Engineering (IJECE) 8, no. 6 (2018): 4673–83. https://doi.org/10.11591/ijece.v8i6.pp4673-4683.

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The healthy food with attention of salt degree is one of the efforts for healthy living of hypertensive patient. The effort is important for reducing the probability of hypertension change to be dangerous disease. In this study, the food composition is build with attention nutrition amount, salt degree, and minimum cost. The proposed method is hybrid method of Genetic Algorithm (GA) and Variable Neighborhood Search (VNS). The three scenarios of hybrid GA-VNS types had been developed in this study. Although hybrid GA and VNS take more time than pure GA or pure VNS but the proposed method give b

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2

Fauziyah, Aprilia Nur, and Wayan Firdaus Mahmudy. "Hybrid Genetic Algorithm for Optimization of Food Composition on Hypertensive Patient." International Journal of Electrical and Computer Engineering (IJECE) 8, no. 6 (2018): 4673. http://dx.doi.org/10.11591/ijece.v8i6.pp4673-4683.

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The healthy food with attention of salt degree is one of the efforts for healthy living of hypertensive patient. The effort is important for reducing the probability of hypertension change to be dangerous disease. In this study, the food composition is build with attention nutrition amount, salt degree, and minimum cost. The proposed method is hybrid method of Genetic Algorithm (GA) and Variable Neighborhood Search (VNS). The three scenarios of hybrid GA-VNS types had been developed in this study. Although hybrid GA and VNS take more time than pure GA or pure VNS but the proposed method give b

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3

Meng, Leilei, Weiyao Cheng, Biao Zhang, Wenqiang Zou, and Peng Duan. "A novel hybrid algorithm of genetic algorithm, variable neighborhood search and constraint programming for distributed flexible job shop scheduling problem." International Journal of Industrial Engineering Computations 15, no. 3 (2024): 813–32. http://dx.doi.org/10.5267/j.ijiec.2024.3.001.

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With a decentral and global economy, distributed scheduling problems are getting a lot of attention. This paper addresses a distributed flexible job shop scheduling problem (DFJSP) with minimizing makespan, in which three subproblems, namely operations sequencing, factory selection and machine selection must be determined. To solve the DFJSP, a novel mixed-integer linear programming (MILP) model is first developed, which can solve the small-scaled instances to optimality. Since the NP-hard characteristic of DFJSP, a hybrid algorithm (GA-VNS-CP) of genetic algorithm (GA), variable neighborhood

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4

Rikatsih, Nindynar, Wayan Firdaus Mahmudy, and Syafrial Syafrial. "Hybrid Real-Coded Genetic Algorithm and Variable Neighborhood Search for Optimization of Product Storage." Journal of Information Technology and Computer Science 4, no. 2 (2019): 166. http://dx.doi.org/10.25126/jitecs.201942111.

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Agricultural product storage has a problem that need to be noticedbecause it has an impact in gaining the profit according to the number ofproducts and the capacity of storage. Inappropriate combination of productcauses high expenses and low profit. To solve the problem, we propose geneticalgorithm (GA) as the optimization method. Although GA is good enough tosolve the problem, GA not always gives an optimum result in complex searchspaces because it is easy to be trapped in local optimum. Therefore, we presenta hybrid real-coded genetic algorithm and Variable Neighborhood Search(HRCGA-VNS) to

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5

Fadah, Isti, Anis Elliyana, Yudha Alif Auliya, Yustri Baihaqi, Muhammad Haidar, and Dhea Milinia Sefira. "A Hybrid Genetic-Variable Neighborhood Algorithm for Optimization of Rice Seed Distribution Cost." Mathematical Modelling of Engineering Problems 9, no. 1 (2022): 36–42. http://dx.doi.org/10.18280/mmep.090105.

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Companies engaged in agro-industry, such as rice seed companies, depend on an efficient distribution process because of the characteristics of rice seed products that are easily damaged and do not last long. The distribution and delivery of goods from the production plant to reach consumers must go through several local distributors in several areas (multi-level) such as distributor centers, retailers, and agents spread across several cities in East Java Province. Determining the distribution network will be more complex when a company produces more than one type of product (multiproduct). Bas

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6

Molla-Alizadeh-Zavardehi, S., R. Tavakkoli-Moghaddam, and F. Hosseinzadeh Lotfi. "Hybrid Metaheuristics for Solving a Fuzzy Single Batch-Processing Machine Scheduling Problem." Scientific World Journal 2014 (2014): 1–10. http://dx.doi.org/10.1155/2014/214615.

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This paper deals with a problem of minimizing total weighted tardiness of jobs in a real-world single batch-processing machine (SBPM) scheduling in the presence of fuzzy due date. In this paper, first a fuzzy mixed integer linear programming model is developed. Then, due to the complexity of the problem, which is NP-hard, we design two hybrid metaheuristics called GA-VNS and VNS-SA applying the advantages of genetic algorithm (GA), variable neighborhood search (VNS), and simulated annealing (SA) frameworks. Besides, we propose three fuzzy earliest due date heuristics to solve the given problem

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7

Li, Jun-Qing, Quan-Ke Pan, and Sheng-Xian Xie. "A hybrid variable neighborhood search algorithm for solving multi-objective flexible job shop problems." Computer Science and Information Systems 7, no. 4 (2010): 907–30. http://dx.doi.org/10.2298/csis090608017l.

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In this paper, we propose a novel hybrid variable neighborhood search algorithm combining with the genetic algorithm (VNS+GA) for solving the multi-objective flexible job shop scheduling problems (FJSPs) to minimize the makespan, the total workload of all machines, and the workload of the busiest machine. Firstly, a mix of two machine assignment rules and two operation sequencing rules are developed to create high quality initial solutions. Secondly, two adaptive mutation rules are used in the hybrid algorithm to produce effective perturbations in machine assignment component. Thirdly, a speed

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8

Joshi, Kanchan, Karuna Jain, and Vijay Bilolikar. "A VNS-GA-based hybrid metaheuristics for resource constrained project scheduling problem." International Journal of Operational Research 27, no. 3 (2016): 437. http://dx.doi.org/10.1504/ijor.2016.078938.

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Jain, Karuna, Vijay Bilolikar, and Kanchan Joshi. "A VNS-GA-based hybrid metaheuristics for resource constrained project scheduling problem." International Journal of Operational Research 27, no. 3 (2016): 437. http://dx.doi.org/10.1504/ijor.2016.10000141.

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10

Maghfiroh, Meilinda Fitriani Nur. "Solving Multi-Objective Paired Single Row Facility Layout Problem Using Hybrid Variable Neighborhood Search." Jurnal Teknik Industri 23, no. 2 (2021): 171–82. http://dx.doi.org/10.9744/jti.23.2.171-182.

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The footwear industry is distinguished by its manual assembly line and a high proportion of shared workstation configuration. This study focuses on a subset of the single row facility layout problem known as the paired single row facility layout problem. As one of type of single-row facility layout, the paired single row facility layout problem cannot be solved quickly. Further, different objectives also need to be considered in the decision-making process. Therefore, multi-objective approaches are proposed to minimize the penalty of material handler usage while maximizing the adjacency functi

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11

Pan, Lihong, Miyuan Shan, and Linfeng Li. "Optimizing Perishable Product Supply Chain Network Using Hybrid Metaheuristic Algorithms." Sustainability 15, no. 13 (2023): 10711. http://dx.doi.org/10.3390/su151310711.

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This paper focuses on optimizing the long- and short-term planning of the perishable product supply chain network (PPSCN). It addresses the integration of strategic location, tactical inventory, and operational routing decisions. Additionally, it takes into consideration the specific characteristics of perishable products, including their shelf life, inventory management, and transportation damages. The main objective is to minimize the overall supply chain cost. To achieve this, a nonlinear mixed integer programming model is developed for the multi-echelon, multi-product, and multi-period loc

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12

Pan, Lihong, and Miyuan Shan. "Optimization of Sustainable Supply Chain Network for Perishable Products." Sustainability 16, no. 12 (2024): 5003. http://dx.doi.org/10.3390/su16125003.

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In today’s perishable products industry, the importance of sustainability as a critical consideration has significantly increased. This study focuses on the design of a sustainable perishable product supply chain network (SPPSCN), considering the factors of economics cost, environmental impacts, and social responsibility. The proposed model is a comprehensive production–location–inventory problem optimization framework that addresses multiple objectives, echelons, products, and periods. To solve this complex problem, we introduce three hybrid metaheuristic algorithms: bat algorithm (BA), shuff

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13

Azzouz, Ameni, Meriem Ennigrou, and Lamjed Ben Said. "A hybrid algorithm for flexible job-shop scheduling problem with setup times." International Journal of Production Management and Engineering 5, no. 1 (2017): 23. http://dx.doi.org/10.4995/ijpme.2017.6618.

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Job-shop scheduling problem is one of the most important fields in manufacturing optimization where a set of n jobs must be processed on a set of m specified machines. Each job consists of a specific set of operations, which have to be processed according to a given order. The Flexible Job Shop problem (FJSP) is a generalization of the above-mentioned problem, where each operation can be processed by a set of resources and has a processing time depending on the resource used. The FJSP problems cover two difficulties, namely, machine assignment problem and operation sequencing problem. This pap

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14

Fuladi, Shubhendu Kshitij, and Chang-Soo Kim. "Dynamic Events in the Flexible Job-Shop Scheduling Problem: Rescheduling with a Hybrid Metaheuristic Algorithm." Algorithms 17, no. 4 (2024): 142. http://dx.doi.org/10.3390/a17040142.

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In the real world of manufacturing systems, production planning is crucial for organizing and optimizing various manufacturing process components. The objective of this paper is to present a methodology for both static scheduling and dynamic scheduling. In the proposed method, a hybrid algorithm is utilized to optimize the static flexible job-shop scheduling problem (FJSP) and dynamic flexible job-shop scheduling problem (DFJSP). This algorithm integrates the genetic algorithm (GA) as a global optimization technique with a simulated annealing (SA) algorithm serving as a local search optimizati

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15

Ebrahimi, Maryam, Parviz Dinari, Mohamad Samaei, Rouhollah Sohrabi, and Soheil Sherafatianfini. "A New Approach Based on the Learning Effect for Sequence-Dependent Parallel Machine Scheduling Problem under Uncertainty." Discrete Dynamics in Nature and Society 2022 (September 10, 2022): 1–9. http://dx.doi.org/10.1155/2022/2648936.

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Production system design has lots of restrictions and complex assumptions that cause difficulty in decision making. One of the most important of them is the complexity of the relationship between man and machine. In this regard, operator learning is recognized as an effective element in completing tasks in the production system. In this research, a mathematical model for scheduling the parallel machines in terms of job degradation and operator learning is presented. As one of the most important assumptions, the sequence-dependent setup time is of concern. In other words, jobs are processed seq

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16

Roberto Costa da Silva, Mauro, and Rafael Crivellari Saliba Schouery. "Local-search based heuristics for advertisement scheduling." RAIRO - Operations Research, May 16, 2024. http://dx.doi.org/10.1051/ro/2024114.

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In the MAXSPACE problem, given a set of ads A, one wants to place a subset A' of A into K slots B_1, ..., B_K of size L. Each ad A_i in A has size s_i and frequency w_i. A schedule is feasible if the total size of ads in any slot is at most L, and each ad A_i in A' appears in exactly w_i slots. The goal is to find a feasible schedule that maximizes the space occupied in all slots. We introduce MAXSPACE-RDWV, a MAXSPACE generalization with release dates, deadlines, variable frequency, and generalized profit. In MAXSPACE-RDWV each ad A_i has a release date r_i >= 1, a deadline d_i >= r_i,

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17

Li, Jiawei, Kunkun Peng, Xudong Deng, Jing Wang, and Ao Liu. "Model and algorithm for pharmaceutical distribution routing problem considering customer priority and carbon emissions." Data-Centric Engineering 5 (2024). http://dx.doi.org/10.1017/dce.2024.13.

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Abstract Pharmaceutical distribution routing problem is a key problem for pharmaceutical enterprises, since efficient schedules can enhance resource utilization and reduce operating costs. Meanwhile, it is a complicated combinatorial optimization problem. Existing research mainly focused on delivery route lengths or distribution costs minimization, while seldom considered customer priority and carbon emissions simultaneously. However, considering the customer priority and carbon emissions simultaneously will not only help to enhance customer satisfaction, but also help to reduce the carbon emi

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18

Wang, Yu, Tao Zhu, Kaibo Yuan, Peiwen Zhang, Zhe Liang, and Jinfu Zhu. "An Interval Integrated Optimization to Air‐Cargo Hub Network Design and Airline Fleet Planning." Journal of Advanced Transportation 2024, no. 1 (2024). http://dx.doi.org/10.1155/2024/5754231.

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The objective of this study is to minimize the overall transportation cost through the joint decision‐making for air‐cargo hub network design and fleet planning under the uncertain environment. This joint decision‐making considers various factors, including hub location, node connectivity, fleet size, and flight frequency. It takes into account several uncertain parameters such as air‐cargo demand and transportation cost in a realistic setting. We propose a mixed‐integer programming model tailored to the characteristics of such problem, which utilizes interval numbers to address these challeng

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19

Kosanoglu, Fuat, Mahir Atmis, and Hasan Hüseyin Turan. "A deep reinforcement learning assisted simulated annealing algorithm for a maintenance planning problem." Annals of Operations Research, March 15, 2022. http://dx.doi.org/10.1007/s10479-022-04612-8.

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AbstractMaintenance planning aims to improve the reliability of assets, prevent the occurrence of asset failures, and reduce maintenance costs associated with downtime of assets and maintenance resources (such as spare parts and workforce). Thus, effective maintenance planning is instrumental in ensuring high asset availability with the minimum cost. Nevertheless, to find such optimal planning is a nontrivial task due to the (i) complex and usually nonlinear inter-relationship between different planning decisions (e.g., inventory level and workforce capacity), and (ii) stochastic nature of the

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