\"A demand exists to contribute towards the widening awareness of the need for sustainable maritime development and for coordinated maritime policies worldwide. Maritime shipping is considered the most eco-efficient mean of transportation and yet, is responsible for negative environmental impacts.
This dissertation focuses on developing data-driven decision support tools to evaluate the sustainable performance of MTS by focusing on the elements of the MTS that place stress on the environment. The first research contribution is a System Dynamics simulation model that examines the MTS resiliency after an extreme event and determines the sequence needed to restore the ocean-going port to its pre-event state. The second is a Decision-Making in Complex Environments (DMCE) tool developed by integrating fuzzy logic with a combination of Analytic Hierarchy Process (FAHP) and Techniques for Order Performance by Similarity to Ideal Solution (FTOPSIS) to quantify and rank preferred environmental impact indicators within MTS. The third is an extension to this DMCE tool by the integration of a Monte Carlo simulation in order to have a better understanding of the risks associated with the resulting rankings of those preferred environmental indicators. And, the fourth is a predictive model for the monitoring of vegetation changes near-port areas and to understand the long-term impacts that maritime activity has towards the environment. The developed models address the impacts MTS has on the natural environment and help achieve environmental sustainability of this complex system by evaluating the sustainability performance of the MTS\"--Abstract, page iv.
","abstract_html":"<p>"A demand exists to contribute towards the widening awareness of the need for sustainable maritime development and for coordinated maritime policies worldwide. Maritime shipping is considered the most eco-efficient mean of transportation and yet, is responsible for negative environmental impacts.</p><p>This dissertation focuses on developing data-driven decision support tools to evaluate the sustainable performance of MTS by focusing on the elements of the MTS that place stress on the environment. The first research contribution is a System Dynamics simulation model that examines the MTS resiliency after an extreme event and determines the sequence needed to restore the ocean-going port to its pre-event state. The second is a Decision-Making in Complex Environments (DMCE) tool developed by integrating fuzzy logic with a combination of Analytic Hierarchy Process (FAHP) and Techniques for Order Performance by Similarity to Ideal Solution (FTOPSIS) to quantify and rank preferred environmental impact indicators within MTS. The third is an extension to this DMCE tool by the integration of a Monte Carlo simulation in order to have a better understanding of the risks associated with the resulting rankings of those preferred environmental indicators. And, the fourth is a predictive model for the monitoring of vegetation changes near-port areas and to understand the long-term impacts that maritime activity has towards the environment. The developed models address the impacts MTS has on the natural environment and help achieve environmental sustainability of this complex system by evaluating the sustainability performance of the MTS"--Abstract, page iv.</p>","abstract_has_math":false,"creators":["Pérez Lespier, Lizzette Marie"],"institution":"Missouri University of Science and Technology","degree_name":"Ph. D. in Engineering Management","degree_level":null,"degree_discipline":null,"degree_department":null,"school":null,"contributors":[],"advisors":[],"committee_chairs":[],"committee_members":[],"year":null,"date_issued":"","date_published":null,"updated_at":"2026-07-24T03:18:34Z","subjects":["Decision-making In Complex Environments","Environmental Sustainability","Fuzzy Logic","Maritime Transportation System","Remote Sensing","System Dynamics","Sustainability","Transportation Engineering"],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://scholarsmine.mst.edu/doctoral_dissertations/2569","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:creator","label":"Author","values":["Pérez Lespier, Lizzette Marie"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:type","label":"Dc Type","values":["Dissertation - Open Access"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Ph. D. in Engineering Management"]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["Missouri University of Science and Technology"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Decision-making In Complex Environments","Environmental Sustainability","Fuzzy Logic","Maritime Transportation System","Remote Sensing","System Dynamics","Sustainability","Transportation Engineering"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://scholarsmine.mst.edu/doctoral_dissertations/2569"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["\"A demand exists to contribute towards the widening awareness of the need for sustainable maritime development and for coordinated maritime policies worldwide. Maritime shipping is considered the most eco-efficient mean of transportation and yet, is responsible for negative environmental impacts.
This dissertation focuses on developing data-driven decision support tools to evaluate the sustainable performance of MTS by focusing on the elements of the MTS that place stress on the environment. The first research contribution is a System Dynamics simulation model that examines the MTS resiliency after an extreme event and determines the sequence needed to restore the ocean-going port to its pre-event state. The second is a Decision-Making in Complex Environments (DMCE) tool developed by integrating fuzzy logic with a combination of Analytic Hierarchy Process (FAHP) and Techniques for Order Performance by Similarity to Ideal Solution (FTOPSIS) to quantify and rank preferred environmental impact indicators within MTS. The third is an extension to this DMCE tool by the integration of a Monte Carlo simulation in order to have a better understanding of the risks associated with the resulting rankings of those preferred environmental indicators. And, the fourth is a predictive model for the monitoring of vegetation changes near-port areas and to understand the long-term impacts that maritime activity has towards the environment. The developed models address the impacts MTS has on the natural environment and help achieve environmental sustainability of this complex system by evaluating the sustainability performance of the MTS\"--Abstract, page iv.
"]},{"key":"dc:title","label":"Title","values":["Environmental hazard identification, assessment and control for a sustainable maritime transportation system"]}]}],"canonical_facts":{"dc:creator":["Pérez Lespier, Lizzette Marie"],"dc:description.abstract":["\"A demand exists to contribute towards the widening awareness of the need for sustainable maritime development and for coordinated maritime policies worldwide. Maritime shipping is considered the most eco-efficient mean of transportation and yet, is responsible for negative environmental impacts.
This dissertation focuses on developing data-driven decision support tools to evaluate the sustainable performance of MTS by focusing on the elements of the MTS that place stress on the environment. The first research contribution is a System Dynamics simulation model that examines the MTS resiliency after an extreme event and determines the sequence needed to restore the ocean-going port to its pre-event state. The second is a Decision-Making in Complex Environments (DMCE) tool developed by integrating fuzzy logic with a combination of Analytic Hierarchy Process (FAHP) and Techniques for Order Performance by Similarity to Ideal Solution (FTOPSIS) to quantify and rank preferred environmental impact indicators within MTS. The third is an extension to this DMCE tool by the integration of a Monte Carlo simulation in order to have a better understanding of the risks associated with the resulting rankings of those preferred environmental indicators. And, the fourth is a predictive model for the monitoring of vegetation changes near-port areas and to understand the long-term impacts that maritime activity has towards the environment. The developed models address the impacts MTS has on the natural environment and help achieve environmental sustainability of this complex system by evaluating the sustainability performance of the MTS\"--Abstract, page iv.
"],"dc:identifier":["https://scholarsmine.mst.edu/doctoral_dissertations/2569"],"dc:subject":["Decision-making In Complex Environments","Environmental Sustainability","Fuzzy Logic","Maritime Transportation System","Remote Sensing","System Dynamics","Sustainability","Transportation Engineering"],"dc:title":["Environmental hazard identification, assessment and control for a sustainable maritime transportation system"],"dc:type":["Dissertation - Open Access"],"thesis:degree_name":["Ph. D. in Engineering Management"],"thesis:institution_name":["Missouri University of Science and Technology"]},"updated_at":"2026-07-24T03:18:34Z"}