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Job Scheduling on Parallel Machines with Precedence Constraints Using Mathematical Formulation and Genetic Algorithm

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Intelligent Control, Robotics, and Industrial Automation (RCAAI 2022)

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 1066))

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Abstract

Jobs need to be scheduled on identical parallel machines and are subjected to machine eligibility restrictions and various complex sequence constraints with the goal of makespan minimization. A mathematical formulation as a Mixed Integer Linear Programming (MILP) is elaborated using two decision variables. The formulation is solved using Integer Programming (IP) solver, which is NP-hard, and there are high chances of not finding an optimal/feasible solution for a bigger data set in the stipulated time. The current article proposes job scheduling using the evolutionary computing approach, specifically the Genetic Algorithm (GA). Simulation experiments are conducted for various scenarios of jobs and machines subjected to different complex constraints. The result of the proposed GA is in good agreement with the results obtained from the IP solver and is achieved at a significantly reduced computational time, especially when a larger number of jobs and machines are involved.

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Author information

Authors and Affiliations

  1. Department of Automation & Robotics, KLE Technological University, Hubballi, 580031, India

    Sachin Karadgi

  2. Master of Computer Applications, KLE Technological University, Hubballi, 580031, India

    P. S. Hiremath

Authors
  1. Sachin Karadgi
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  2. P. S. Hiremath
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Corresponding author

Correspondence to Sachin Karadgi .

Editor information

Editors and Affiliations

  1. School of Engg., Computing and Math.,, University of Plymouth, Plymouth, UK

    Sanjay Sharma

  2. School of Electrical Sciences, Indian Institute of Technology Goa, Ponda, Goa, India

    Bidyadhar Subudhi

  3. Department of Mechatronics, Manipal Institute of Technology, Manipal, Karnataka, India

    Umesh Kumar Sahu

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Karadgi, S., Hiremath, P.S. (2023). Job Scheduling on Parallel Machines with Precedence Constraints Using Mathematical Formulation and Genetic Algorithm. In: Sharma, S., Subudhi, B., Sahu, U.K. (eds) Intelligent Control, Robotics, and Industrial Automation. RCAAI 2022. Lecture Notes in Electrical Engineering, vol 1066. Springer, Singapore. https://doi.org/10.1007/978-981-99-4634-1_65

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