A two-stage fuzzy robust integer programming approach for capacity planning of environmental management systems
In this study, a two-stage fuzzy robust integer programming (TFRIP) method has been developed for planning environmental management systems under uncertainty. This approach integrates techniques of robust programming and two-stage stochastic programming within a mixed integer linear programming fram...
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| Veröffentlicht in: | European journal of operational research 2008-09, Vol.189 (2), p.399-420 |
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| container_title | European journal of operational research |
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| creator | Li, Y.P. Huang, G.H. Nie, X.H. Nie, S.L. |
| description | In this study, a two-stage fuzzy robust integer programming (TFRIP) method has been developed for planning environmental management systems under uncertainty. This approach integrates techniques of robust programming and two-stage stochastic programming within a mixed integer linear programming framework. It can facilitate dynamic analysis of capacity-expansion planning for waste management facilities within a multi-stage context. In the modeling formulation, uncertainties can be presented in terms of both possibilistic and probabilistic distributions, such that robustness of the optimization process could be enhanced. In its solution process, the fuzzy decision space is delimited into a more robust one by specifying the uncertainties through dimensional enlargement of the original fuzzy constraints. The TFRIP method is applied to a case study of long-term waste-management planning under uncertainty. The generated solutions for continuous and binary variables can provide desired waste-flow-allocation and capacity-expansion plans with a minimized system cost and a maximized system feasibility. |
| doi_str_mv | 10.1016/j.ejor.2007.05.014 |
| format | Article |
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This approach integrates techniques of robust programming and two-stage stochastic programming within a mixed integer linear programming framework. It can facilitate dynamic analysis of capacity-expansion planning for waste management facilities within a multi-stage context. In the modeling formulation, uncertainties can be presented in terms of both possibilistic and probabilistic distributions, such that robustness of the optimization process could be enhanced. In its solution process, the fuzzy decision space is delimited into a more robust one by specifying the uncertainties through dimensional enlargement of the original fuzzy constraints. The TFRIP method is applied to a case study of long-term waste-management planning under uncertainty. The generated solutions for continuous and binary variables can provide desired waste-flow-allocation and capacity-expansion plans with a minimized system cost and a maximized system feasibility.</description><subject>Applied sciences</subject><subject>Decision making models</subject><subject>Decision theory. Utility theory</subject><subject>Decision-making</subject><subject>Environment</subject><subject>Environmental management</subject><subject>Exact sciences and technology</subject><subject>Fuzzy logic</subject><subject>Integer programming</subject><subject>Linear programming</subject><subject>Mathematical programming</subject><subject>Operational research and scientific management</subject><subject>Operational research. Management science</subject><subject>Planning</subject><subject>Robust programming</subject><subject>Stochastic models</subject><subject>Studies</subject><subject>Two-stage stochastic</subject><subject>Uncertainty</subject><subject>Waste disposal</subject><issn>0377-2217</issn><issn>1872-6860</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2008</creationdate><recordtype>article</recordtype><sourceid>X2L</sourceid><recordid>eNp9UE1r3DAQNaWFbtP-gZ5EoUc7-rAtG3oJoWlLAr3kLmbl8UZmLbmSdovz6ztmQ44VjGaGee_N8Iris-CV4KK9niqcQqwk57riTcVF_abYiU7Lsu1a_rbYcaV1KaXQ74sPKU2cc9GIZleEG5b_hjJlOCAbT8_PK4thf0qZOZ_xgJEtMRwizLPzBwYLdWCf2Bgis7CAdXllyxG838ZhZOjPLgY_o89wZDN40t0altaUcU4fi3cjHBN-eslXxePd98fbn-XD7x-_bm8eSlvrPpf7EZXVQkInR-i7WmGj9y1oPeihFjjAYLFWdbeNrKK-6_QgsG_7HkEqdVV8ucjSvX9OmLKZwil62mgkr0WteNsTSF5ANoaUIo5miW6GuBrBzWarmcxmq9lsNbwxZCuR7i-kiAvaVwbSIygmczYKRNfTv1IQtaPktpJioVB9b2rJzVOeSe3ry52QLBzHCN669Koq-bZaCcJ9u-CQPDs7jCZZh97i4CLabIbg_nf0Pzoqqhg</recordid><startdate>20080901</startdate><enddate>20080901</enddate><creator>Li, Y.P.</creator><creator>Huang, G.H.</creator><creator>Nie, X.H.</creator><creator>Nie, S.L.</creator><general>Elsevier B.V</general><general>Elsevier</general><general>Elsevier Sequoia S.A</general><scope>IQODW</scope><scope>DKI</scope><scope>X2L</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>7TB</scope><scope>8FD</scope><scope>FR3</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope></search><sort><creationdate>20080901</creationdate><title>A two-stage fuzzy robust integer programming approach for capacity planning of environmental management systems</title><author>Li, Y.P. ; Huang, G.H. ; Nie, X.H. ; Nie, S.L.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c479t-bfe3c712a82fa9843e57b6a77d7d41edadce43489843c3eda887d1e9699ea233</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2008</creationdate><topic>Applied sciences</topic><topic>Decision making models</topic><topic>Decision theory. Utility theory</topic><topic>Decision-making</topic><topic>Environment</topic><topic>Environmental management</topic><topic>Exact sciences and technology</topic><topic>Fuzzy logic</topic><topic>Integer programming</topic><topic>Linear programming</topic><topic>Mathematical programming</topic><topic>Operational research and scientific management</topic><topic>Operational research. Management science</topic><topic>Planning</topic><topic>Robust programming</topic><topic>Stochastic models</topic><topic>Studies</topic><topic>Two-stage stochastic</topic><topic>Uncertainty</topic><topic>Waste disposal</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Li, Y.P.</creatorcontrib><creatorcontrib>Huang, G.H.</creatorcontrib><creatorcontrib>Nie, X.H.</creatorcontrib><creatorcontrib>Nie, S.L.</creatorcontrib><collection>Pascal-Francis</collection><collection>RePEc IDEAS</collection><collection>RePEc</collection><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><jtitle>European journal of operational research</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Li, Y.P.</au><au>Huang, G.H.</au><au>Nie, X.H.</au><au>Nie, S.L.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A two-stage fuzzy robust integer programming approach for capacity planning of environmental management systems</atitle><jtitle>European journal of operational research</jtitle><date>2008-09-01</date><risdate>2008</risdate><volume>189</volume><issue>2</issue><spage>399</spage><epage>420</epage><pages>399-420</pages><issn>0377-2217</issn><eissn>1872-6860</eissn><coden>EJORDT</coden><abstract>In this study, a two-stage fuzzy robust integer programming (TFRIP) method has been developed for planning environmental management systems under uncertainty. This approach integrates techniques of robust programming and two-stage stochastic programming within a mixed integer linear programming framework. It can facilitate dynamic analysis of capacity-expansion planning for waste management facilities within a multi-stage context. In the modeling formulation, uncertainties can be presented in terms of both possibilistic and probabilistic distributions, such that robustness of the optimization process could be enhanced. In its solution process, the fuzzy decision space is delimited into a more robust one by specifying the uncertainties through dimensional enlargement of the original fuzzy constraints. The TFRIP method is applied to a case study of long-term waste-management planning under uncertainty. The generated solutions for continuous and binary variables can provide desired waste-flow-allocation and capacity-expansion plans with a minimized system cost and a maximized system feasibility.</abstract><cop>Amsterdam</cop><pub>Elsevier B.V</pub><doi>10.1016/j.ejor.2007.05.014</doi><tpages>22</tpages></addata></record> |
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| ispartof | European journal of operational research, 2008-09, Vol.189 (2), p.399-420 |
| issn | 0377-2217 1872-6860 |
| language | eng |
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| source | RePEc; ScienceDirect Journals (5 years ago - present) |
| subjects | Applied sciences Decision making models Decision theory. Utility theory Decision-making Environment Environmental management Exact sciences and technology Fuzzy logic Integer programming Linear programming Mathematical programming Operational research and scientific management Operational research. Management science Planning Robust programming Stochastic models Studies Two-stage stochastic Uncertainty Waste disposal |
| title | A two-stage fuzzy robust integer programming approach for capacity planning of environmental management systems |
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