What is it about?
The goal of this paper is to assess the Python computing time to solve a single row facility layout problem (SRFLP) by Simulated Annealing. The optimization problem is introduced, systematically modeled and then optimized numerically using a particular Python framework. The computing time and the results of experiments with various problem sizes and parameters are analyzed and discussed.
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Why is it important?
Python is used more and more as a lightweight and rather simple language to solve larger mathematical problems. Knowing how it behaves with increasingly complex problems is an important factor to chose a technology.
Perspectives
A benchmark study analyzing how the performance of the simulated annealing algorithm evolves when the parameters of a single row facility layout problem are changed. The problem is solved using Python as a programming language.
Alexandre Miccoli
Fachhochschule Nordwestschweiz
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This page is a summary of: Analyzing the Computing Time to Solve Single Row Facility Layout Problems by Simulated Annealing in a Python Framework, April 2023, ACM (Association for Computing Machinery),
DOI: 10.1145/3596947.3596953.
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