{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/66788"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/66788","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Integer Programming Heuristics for Large Capital Budgeting Problems","abstract":"The subject matter of this thesis was the comparison of five integer algorithms suitable for solving large capital budgeting problems such as those characterized by the national development plans in developing nations. In order to obtain statistically meaningful results, we designed and carried out some nonparametric randomized complete block experiments using real world data from the 1968/69 Nigerian national development plan.","abstract_html":"The subject matter of this thesis was the comparison of five integer algorithms suitable for solving large capital budgeting problems such as those characterized by the national development plans in developing nations. In order to obtain statistically meaningful results, we designed and carried out some nonparametric randomized complete block experiments using real world data from the 1968/69 Nigerian national development plan.","abstract_has_math":false,"creators":["Agori-Iwe, Kesiena Oghenemado"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"Ph.D.","degree_level":"Dissertation","degree_discipline":"Agricultural Economics","degree_department":null,"school":null,"contributors":[],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2014,"date_issued":"2014-12-13T19:23:38Z","date_published":"2014-12-13T19:23:38Z","updated_at":"2026-07-22T22:25:56Z","subjects":["Economics, Agricultural"],"languages":["eng"],"rights":[],"rights_urls":[],"identifier_entries":[{"key":"dc:identifier","label":"Identifier","values":["(UMI)AAI8203390"],"render_values":[{"text":"(UMI)AAI8203390","href":null,"code":true}]}]},"links":{"outbound_url":"http://hdl.handle.net/2142/66788","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:creator","label":"Author","values":["Agori-Iwe, Kesiena Oghenemado"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2014-12-13T19:23:38Z","10000-01-01","1981"]},{"key":"dc:type","label":"Dc Type","values":["text"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Agricultural Economics"]},{"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":["Economics, Agricultural"]}]},{"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/2142/66788","(UMI)AAI8203390"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["The subject matter of this thesis was the comparison of five integer algorithms suitable for solving large capital budgeting problems such as those characterized by the national development plans in developing nations. In order to obtain statistically meaningful results, we designed and carried out some nonparametric randomized complete block experiments using real world data from the 1968/69 Nigerian national development plan.","Our results indicate that there is a negative correlation between the solution time and the relative accuracy of the algorithms. The heuristic or approximative algorithms were generally much faster in obtaining results than the exact algorithm. Although the fastest of these algorithms, the Effective Gradient Method, also had the largest relative error, none of the heuristic algorithms returned a relative error of more than 7.0 per cent for the 10 subsets of 100 variables drawn from 1000 variables in the experiments.","A new heuristic algorithm, the Pseudo Reduction Method, which was developed in this study to exploit the special structure of the bounded variable knapsack problem which was exhibited in the development plan, returned more accurate and faster solutions when compared with the Kochenberger/McCarl/Wyman algorithm, another method which was originally designed to solve bounded or general integer variable problems.","Made available in DSpace on 2014-12-13T19:23:38Z (GMT). No. of bitstreams: 1 8203390.pdf: 3330248 bytes, checksum: 6f583817e0cd3380bdf2ce14580a93b5 (MD5) Previous issue date: 1981","Embargo set by: Seth Robbins for item 66966 Lift date: Forever Reason: Restricted to the U of I community idenfinitely during batch ingest of legacy ETDs","Restricted to the U of I community idenfinitely during batch ingest of legacy ETDs","U of I Only","116 p.","Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 1981."]},{"key":"dc:title","label":"Title","values":["Integer Programming Heuristics for Large Capital Budgeting Problems"]}]}],"canonical_facts":{"dc:creator":["Agori-Iwe, Kesiena Oghenemado"],"dc:date":["2014-12-13T19:23:38Z","10000-01-01","1981"],"dc:description":["The subject matter of this thesis was the comparison of five integer algorithms suitable for solving large capital budgeting problems such as those characterized by the national development plans in developing nations. In order to obtain statistically meaningful results, we designed and carried out some nonparametric randomized complete block experiments using real world data from the 1968/69 Nigerian national development plan.","Our results indicate that there is a negative correlation between the solution time and the relative accuracy of the algorithms. The heuristic or approximative algorithms were generally much faster in obtaining results than the exact algorithm. Although the fastest of these algorithms, the Effective Gradient Method, also had the largest relative error, none of the heuristic algorithms returned a relative error of more than 7.0 per cent for the 10 subsets of 100 variables drawn from 1000 variables in the experiments.","A new heuristic algorithm, the Pseudo Reduction Method, which was developed in this study to exploit the special structure of the bounded variable knapsack problem which was exhibited in the development plan, returned more accurate and faster solutions when compared with the Kochenberger/McCarl/Wyman algorithm, another method which was originally designed to solve bounded or general integer variable problems.","Made available in DSpace on 2014-12-13T19:23:38Z (GMT). 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