Physical programming: A review of the state of the art

dc.contributor.authorIlgin M.A.
dc.contributor.authorGupta S.M.
dc.date.accessioned2025-04-10T11:14:51Z
dc.date.available2025-04-10T11:14:51Z
dc.date.issued2012
dc.description.abstractMost traditional multi-criteria optimization techniques require that the decision maker construct an aggregate objective function using the weights determined as a result of a trial and error process. Physical programming (PP) eliminates this tedious weight assignment process by providing decision makers with a flexible and more natural problem formulation. In PP, the decision maker specifies ranges of different degrees of desirability instead of defining weights. In this paper, we present a comprehensive review of PP studies by classifying them into four major categories (viz., methodological papers, industrial engineering applications, mechanical engineering applications and other applications). Insights from the review and future research directions conclude the paper.
dc.identifier.DOI-ID10.24846/v21i4y201201
dc.identifier.urihttp://hdl.handle.net/20.500.14701/50554
dc.publisherNational Institute for R and D in Informatics
dc.titlePhysical programming: A review of the state of the art
dc.typeArticle

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