Modeling and design of material recovery facilities : genetic algorithm approach
Name
920691527-MIT.pdf
Description
Full printable version
Size
17.26 MB
Format
Adobe PDF
Checksum (MD5)
1dfb5a0a1dc91b0bdf532d088af4c762
Author(s)
Testa, Mariapaola
Advisor(s)
Stephen C. Graves.
Alternative Title
Material recovery facilities : genetic algorithm approach
Date Issued
2015
Publisher
Massachusetts Institute of Technology
Abstract
In the Organisation for Economic Co-operation and Development (OECD) area, the production of numerical solid waste (MI\SW) increased by 32% between 1990 and 2011, exceeding 660 million tonnes in 2011; the world-wide production of waste is estimated to grow further due to increasing GDP in developing economies. Given this scenario, effective treatment and recovery of wastes becomes a priority. In developed countries, MSW is usually sent to materials recovery facilities (MRFs), which use mechanical and manual sorting units to extract valuable components. In this work, we define a network flow model to represent a MRF that sorts wastes using multi-output units with recirculating streams. For each material in the system, we define a matrix to describe the sorting process. We then formulate a genetic algorithm (GA) that generates alternative configurations of a MRF having a given set of sorting units with known separation parameters and selects those with highest profit and efficiency. The GA incorporates a heuristic for personnel allocation to manual units. We code the algorithm in Java and apply it to an existing MRF. The results show a 33.4% improvement in profit and a 1.7% improvement in efficiency with respect to the current configuration without hand sorting; and a 6.7% improvement in profit and a 3.9% improvement il efficiency, with respect to the current configuration with hand sorting.
Description
Thesis: S.M., Massachusetts Institute of Technology, Sloan School of Management, Operations Research Center, 2015.
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 187-193).
Subjects
Operations Research Center.
MIT Department
Massachusetts Institute of Technology. Operations Research Center
Sloan School of Management
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