Open AccessA Monte Carlo Simulation-Based Approach to Solve Dynamic Sectorization Problem
Author(s) -
Aydin Teymourifar,
Ana Maria Rodrigues,
José Soeiro Ferreira
Publication year - 2021
Publication title -
mapta journal of mechanical and industrial engineering
Language(s) - English
Resource type - Journals
ISSN - 2517-4258
DOI - 10.33544/mjmie.v5i2.179
Subject(s) - monte carlo method , python (programming language) , mathematical optimization , computer science , stochastic simulation , function (biology) , mathematics , statistics , evolutionary biology , biology , operating system
In this study, two novel stochastic models are introduced to solve the dynamic sectorization problem, in which sectors are created by assigning points to service centres. The objective function of the first model is defined based on the equilibration of the distance in the sectors, while in the second one, it is based on the equilibration of the demands of the sectors. Both models impose constraints on assignments and compactness of sectors. In the problem, the coordinates of the points and their demand change over time, hence it is called a dynamic problem. A new solution method is used to solve the models, in which expected values of the coordinates of the points and their demand are assessed by using the Monte Carlo simulation. Thus, the problem is converted into a deterministic one. The linear and deterministic type of the model, which is originally non-linear is implemented in Python's Pulp library and in this way the generated benchmarks are solved. Information about how benchmarks are derived and the obtained solutions are presented.