Solving multi-objective MILP problems in process synthesis using the multi-criteria branch and bound algorithm

Mavrotas, G; Diakoulaki, D

dc.contributor.author	Mavrotas, G	en
dc.contributor.author	Diakoulaki, D	en
dc.date.accessioned	2014-03-01T01:23:05Z
dc.date.available	2014-03-01T01:23:05Z
dc.date.issued	2005	en
dc.identifier.issn	0930-7516	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/16810
dc.subject	Branch and Bound Algorithm	en
dc.subject	Process Synthesis	en
dc.subject.classification	Engineering, Chemical	en
dc.subject.other	Algorithms	en
dc.subject.other	Integer programming	en
dc.subject.other	Linear programming	en
dc.subject.other	Mathematical models	en
dc.subject.other	Nonlinear programming	en
dc.subject.other	Optimization	en
dc.subject.other	Problem solving	en
dc.subject.other	Synthesis (chemical)	en
dc.subject.other	Mixed integer linear programming (MILP)	en
dc.subject.other	Mixed integer non-linear programming (MINLP)	en
dc.subject.other	Multi-objective programming problem	en
dc.subject.other	Process synthesis	en
dc.subject.other	Vector maximization algorithm	en
dc.subject.other	Chemical engineering	en
dc.subject.other	algorithm	en
dc.title	Solving multi-objective MILP problems in process synthesis using the multi-criteria branch and bound algorithm	en
heal.type	journalArticle	en
heal.identifier.primary	10.1002/ceat.200500135	en
heal.identifier.secondary	http://dx.doi.org/10.1002/ceat.200500135	en
heal.language	English	en
heal.publicationDate	2005	en
heal.abstract	The paper briefly describes the problem of process synthesis in the area of chemical engineering, and suggests its formulation as a Multi-Objective Programming problem. Process synthesis optimization is usually modeled as Mixed Integer Linear Programming (MILP) or Mixed Integer Non-Linear Programming (MINLP) with an economic objective function. We claim that incorporating more criteria (e.g., environmental criteria) in this kind of combinatorial optimization problem offers the decision makers the opportunity to refine their final decision by examining more than one solution (a set of efficient or Pareto optimal solutions instead of one optimal solution). For solving the multi-objective process synthesis problem, an improved version of the Multi-Criteria Branch and Bound (MCBB) algorithm, which has been developed by the same authors, is used. MCBB is a vector maximization algorithm capable of deriving all efficient points (supported and unsupported), for small and medium sized Multi-Objective MILP problems. The application of MCBB in two examples from process synthesis is also presented. © 2005 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.	en
heal.publisher	WILEY-V C H VERLAG GMBH	en
heal.journalName	Chemical Engineering and Technology	en
dc.identifier.doi	10.1002/ceat.200500135	en
dc.identifier.isi	ISI:000234037500005	en
dc.identifier.volume	28	en
dc.identifier.issue	12	en
dc.identifier.spage	1500	en
dc.identifier.epage	1510	en