{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/66896"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/66896","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Methods for Generating Alternative Solutions to Environmental Planning Problems","abstract":"An optimization model is not a perfect representation of a complex environmental planning problem because not all important objectives can be captured in a model. Optimization models can be used in a planning process to generate planning alternatives that are good and different so that the analyst and the decision maker can examine a wide range of alternatives to gain insight and understanding. Modeling to generate alternatives (MGA) is designed to serve this purpose. Several MGA methods, a random method, a generating and screening (G&S) method and a Fuzzy HSJ method, are developed in this dissertation. This work also provides an assessment of the potential use of these MGA methods and an HSJ method for generating good and different alternative solutions; the methods are illustrated using a land use planning problem and a solid waste problem, which are formulated as linear programming models, and a wastewater treatment system planning problem, which is formulated as a mixed integer programming (MIP) model. The results show that various attractive and different plans for the problems can be obtained by using the above approaches.","abstract_html":"An optimization model is not a perfect representation of a complex environmental planning problem because not all important objectives can be captured in a model. Optimization models can be used in a planning process to generate planning alternatives that are good and different so that the analyst and the decision maker can examine a wide range of alternatives to gain insight and understanding. Modeling to generate alternatives (MGA) is designed to serve this purpose. Several MGA methods, a random method, a generating and screening (G&S) method and a Fuzzy HSJ method, are developed in this dissertation. This work also provides an assessment of the potential use of these MGA methods and an HSJ method for generating good and different alternative solutions; the methods are illustrated using a land use planning problem and a solid waste problem, which are formulated as linear programming models, and a wastewater treatment system planning problem, which is formulated as a mixed integer programming (MIP) model. The results show that various attractive and different plans for the problems can be obtained by using the above approaches.","abstract_has_math":false,"creators":["Chang, Shoou-Yuh"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"Ph.D.","degree_level":"Dissertation","degree_discipline":"Environmental Engineering","degree_department":null,"school":null,"contributors":[],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2014,"date_issued":"2014-12-13T19:32:11Z","date_published":"2014-12-13T19:32:11Z","updated_at":"2026-07-22T22:25:56Z","subjects":["Engineering, Sanitary and Municipal"],"languages":["eng"],"rights":[],"rights_urls":[],"identifier_entries":[{"key":"dc:identifier","label":"Identifier","values":["(UMI)AAI8127562"],"render_values":[{"text":"(UMI)AAI8127562","href":null,"code":true}]}]},"links":{"outbound_url":"http://hdl.handle.net/2142/66896","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:creator","label":"Author","values":["Chang, Shoou-Yuh"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2014-12-13T19:32:11Z","10000-01-01","1981"]},{"key":"dc:type","label":"Dc Type","values":["text"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Environmental Engineering"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Dissertation"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Ph.D."]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Illinois at Urbana-Champaign"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Engineering, Sanitary and Municipal"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["eng"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["http://hdl.handle.net/2142/66896","(UMI)AAI8127562"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["An optimization model is not a perfect representation of a complex environmental planning problem because not all important objectives can be captured in a model. Optimization models can be used in a planning process to generate planning alternatives that are good and different so that the analyst and the decision maker can examine a wide range of alternatives to gain insight and understanding. Modeling to generate alternatives (MGA) is designed to serve this purpose. Several MGA methods, a random method, a generating and screening (G&S) method and a Fuzzy HSJ method, are developed in this dissertation. This work also provides an assessment of the potential use of these MGA methods and an HSJ method for generating good and different alternative solutions; the methods are illustrated using a land use planning problem and a solid waste problem, which are formulated as linear programming models, and a wastewater treatment system planning problem, which is formulated as a mixed integer programming (MIP) model. The results show that various attractive and different plans for the problems can be obtained by using the above approaches.","Made available in DSpace on 2014-12-13T19:32:11Z (GMT). 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Optimization models can be used in a planning process to generate planning alternatives that are good and different so that the analyst and the decision maker can examine a wide range of alternatives to gain insight and understanding. Modeling to generate alternatives (MGA) is designed to serve this purpose. Several MGA methods, a random method, a generating and screening (G&S) method and a Fuzzy HSJ method, are developed in this dissertation. This work also provides an assessment of the potential use of these MGA methods and an HSJ method for generating good and different alternative solutions; the methods are illustrated using a land use planning problem and a solid waste problem, which are formulated as linear programming models, and a wastewater treatment system planning problem, which is formulated as a mixed integer programming (MIP) model. 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