Search Results - (( machine scheduling algorithm ) OR ( machine mining algorithm ))

Data Mining On Machine Breakdowns And Effectiveness Of Scheduled Maintenance by Tan, Su Sze

“…Last but not least, some of the complex data mining tasks are not able to perform because of the limited algorithms and machine learning in Orange software.…”
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Solving single machine scheduling problem with maximum lateness using a genetic algorithm by Nazif, Habibeh, Lee, Lai Soon

“…We develop an optimised crossover operator designed by an undirected bipartite graph within a genetic algorithm for solving a single machine family scheduling problem, where jobs are partitioned into families and setup time is required between these families. …”
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Development of Simulated Annealing Based Scheduling Algorithm for Two Machines Flow Shop Problem by M., Muziana, Kamal Z., Zamli

“…Viewing as optimization problem and focusing on two machines, this research aims to develop a new Simulated Annealing based scheduling algorithm, called SA2M, for flow shop problem. …”
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Hybrid flow shop scheduling with energy consumption in machine shop using moth flame optimization by M. F. F., Ab Rashid, Ahmad Nasser, Mohd Rose, N. M. Zuki, N. M.

“…The objectives were to optimize makespan and total energy consumption in the machine schedule. Optimization using MFO has been conducted and the results was compared with well-established algorithm like Genetic Algorithm, Ant Colony Optimization and Particle Swarm Optimization. …”
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A genetic algorithm on single machine family scheduling problem to minimise total weighted completion time by Nazif, Habibeh, Lee, Lai Soon

“…In this paper, we address a single machine family scheduling problem where jobs, each characterised by a processing time and an associated positive weight, are partitioned into families and setup time is required between these families. …”
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An efficient VM scheduling algorithm to minimize the makespan and maximize the profit by Ibrahim, Aws Fadhil

“…The second process is hyper analytical task scheduling algorithm, and based on the scheduled task, the policy based profit maximization algorithm was proposed in final process. …”
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Comparative study on job scheduling using priority rule and machine learning by Murad, Saydul Akbar, Zafril Rizal, M Azmi, Abu Jafar, Md Muzahid, Al-Imran, Md.

“…We’ve achieved better for SJF and a decent machine learning algorithm outcome as well.…”
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Flexible job shop scheduling using priority heuristics and genetic algorithm by Farashahi, Hamid Ghaani

“…The job shop scheduling is very common in practice and uniform machines (parallel machines with different speeds) have been used in job shop environment for flexibility. …”
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Optimization of Simultaneous Scheduling for Machines and Automated Guided Vehicles Using Fuzzy Genetic Algorithm by Badakhshian, Mostafa

“…Genetic algorithm (GA) proposed as a robust tool for optimization of scheduling problems. …”
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Adaptive intelligence job online scheduling within dynamic grid environment based on gridsim by Lorpunmanee, Siriluck, Md. Sap, Mohd. Noor, Abdullah, Abdul Hanan

“…The idea behind the adaptive job scheduling algorithm is the hybrid algorithms that consist of Ant Colony Optimization (ACO) and Tabu algorithms. …”
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Optimization of hybrid flow shop scheduling in a machine shop: Achieving energy efficiency and minimizing machine idleness with multi-objective Tiki Taka optimization by Siti Nurhazwani Husna, Mohd Hata, Muhammad Ammar, Nik Mu’tasim, Mohd Fadzil Faisae, Ab Rashid

“…The study considered machine idle time as a key factor influencing energy efficiency, incorporating it into the scheduling evaluation. …”
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Hybrid dynamic scheduling model for flexible manufacturing system with machine availability and new job arrivals by Paslar, Shahla

“…The performance of the schedules as produced by the scheduling/rescheduling algorithms were investigated and compared. …”
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The optimization inventory process on identical machine job shop with multiple setups using genetic algorithm by Abd Rahman, Md Nizam, Irwan, Hery, Ebrahim, Zuhriah, Leuveano, Raden Achmad Chairdino, Dzakiyullah, Nur Rachman

“…Given that job shop scheduling with multiple machines, products, and setups is an NP-hard problem, this study will employ a genetic algorithm for the optimization process. …”
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Machine Learning Algorithms for Diabetes Prediction: A Review Paper by Al-Sideiri A., Cob Z.B.C., Drus S.B.M.

“…Computer aided diagnosis; Data mining; Learning systems; Patient treatment; Predictive analytics; Robotics; Support vector machines; Data mining algorithm; Diabetes mellitus; Early diagnosis; Knowledge accumulation; Literature reviews; Prediction techniques; Review papers; Support vector machine algorithm; Learning algorithms…”

Performance optimization of simultaneous machine and automated guided vehicle scheduling using fuzzy logic controller based genetic algorithm. by Sulaiman, Shamsuddin, Mohd Ariffin, Mohd Khairol Anuar, Badakshian, Mostafa

“…One of the automatedmaterials handling equipment in FMS is automated guided vehicles (AGVs). Integrated scheduling ofAGVs and machines is an essential factor contributing to the efficiency of the manufacturing system inFMS environment. …”
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ROA-CONS: raccoon optimization job scheduling by Koohi, Sina Zangbari, Abdul Hamid, Nor Asilah Wati, Othman, Mohamed, Ibragimov, Gafurjan

“…An optimised schedule results in greater efficiency of the parallel machine. …”
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Guided genetic algorithm for solving unrelated parallel machine scheduling problem with additional resources by Abed, Munther Hameed, Mohd Nizam Mohmad, Kahar

“…This paper solved the unrelated parallel machine scheduling with additional resources (UPMR) problem. …”
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Scheduling With Alternatives Machine Using Fuzzy Inference System And Genetic Algorithm. by Kamaruddin, Shahrul, Mokhtar, Mohzani, Subari, Khairanum, Othman, Zalinda

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Hybridizing guided genetic algorithm and single-based metaheuristics to solve unrelated parallel machine scheduling problem with scarce resources by Abed, Munther H., Mohd Nizam, Mohmad Kahar

“…This paper focuses on solving unrelated parallel machine scheduling with resource constraints (UPMR). …”
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Optimization ofhybrid flow shop scheduling in a machine shop: Achieving energy efficiency and minimizing machine idleness with multi-objective Tiki Taka optimization by Siti Nurhazwani Husna, Mohd Hata, Muhammad Ammar, Nik Mu’tasim, Mohd Fadzil Faisae, Ab Rashid

“…A case study was conducted using fourteen jobs across three stages, which involved the use oflathes, millingmachines, and deburring machines. The EE-HFS was optimized using Multi-Objective Tiki Taka Optimization (MOTTA).The study considered machine idle time as a key factor influencing energy efficiency, incorporating it into the scheduling evaluation.The optimization result was compared to established algorithms, such as the Non-dominated Sorting Genetic Algorithm-II, the Multi-ObjectiveEvolutionary Algorithm Based on Decomposition, the Multi-ObjectiveParticle Swarm Optimization,and the recent algorithm,the Multi-ObjectiveGrey Wolf Optimizer. …”
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