Genetic Algorithms for Solving Scheduling Problems in Manufacturing Systems

  title={Genetic Algorithms for Solving Scheduling Problems in Manufacturing Systems},
  author={Anna Ławrynowicz},
Genetic Algorithms for Solving Scheduling Problems in Manufacturing Systems Scheduling manufacturing operations is a complicated decision making process. From the computational point of view, the scheduling problem is one of the most notoriously intractable NP-hard optimization problems. When the manufacturing system is not too large, the traditional methods for solving scheduling problem proposed in the literature are able to obtain the optimal solution within reasonable time. But its… 


A new optimization technique called Dragonfly Algorithm (DA) is implemented for optimum scheduling of Multi objective Scheduling problems considered from the literature and the results obtained are very competitive when compared with other well-known algorithms like Genetic Algorithm, Particle Swarm Optimization, Cuckoo Search, Modified Cuckoos Search & Jaya Algorithms.

Genetic algorithms for the scheduling in additive manufacturing

Genetic Algorithms (GAs) are introduced to tackle the packing problem. The scheduling in Additive Manufacturing (AM) is also dealt with to set up a managed market, called “Lonja3D”. This will enable

Examinations Timetabling System Based on A Genetic Algorithm

A computer-based application is designed to generate an automated exam scheduler that was implemented on the data collected from the Faculty of Science at Omar Al-Mukhtar University and a genetic algorithm based on a strategy for generating examination schedules that prioritize students’ achievement while meeting the hard constraints required for feasibility is proposed.

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Solving Power Battery Scheduling Problem Based on TSP

  • Janxin ZhouX. YaoNing Zhou
  • Business
    2018 IEEE 3rd Advanced Information Technology, Electronic and Automation Control Conference (IAEAC)
  • 2018
Experimental results show that the genetic algorithm can effectively improve the operating efficiency of RGV and minimize the task time and establish a model.

Genetic Algorithm as Automated Valuation Model Component in Real Estate Investment Decisions System

Abstract Every real-estate related investment decision making process calls for the careful analysis of available information even though it is often carried out in conditions of uncertainty. The

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Every real estate investment decision making, because of the high capital-intensive character of properties, requires careful analysis of information. Availability of the information, market

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A method which can extract effective information only from the pictures to solve the problem that the pavement model cannot be established in ADAMS due to the inability of field measurement and the lack of drawings.

Microsoft Word-5983092022138444001.docx

  • 2022



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