Topic
Goal programming
About: Goal programming is a research topic. Over the lifetime, 4330 publications have been published within this topic receiving 117758 citations.
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01 Jan 1978
TL;DR: The past decade has seen a dramatic increase in research on all main areas of multiple criteria decision-making, including formal models of multicriterion choice, multicriteria evaluation theories, and multi-criteria assessment methodologies as mentioned in this paper.
Abstract: The past decade has seen a dramatic increase in research on all main areas of multiple criteria decision making, including formal models of multicriterion choice, multicriterion evaluation theories, and multicriterion assessment methodologies.
50 citations
TL;DR: A hierarchical methodology for the design of manufacturing cells is proposed, which includes labour-grouping considerations in addition to partmachine grouping, and synthesizes the capabilities of neural network methods for rapid clustering of large partmachine data sets with multi-objective optimization capabilities of mathematical programming.
Abstract: A hierarchical methodology for the design of manufacturing cells is proposed, which includes labour-grouping considerations in addition to partmachine grouping. It is empirically driven and designed for an interactive decision environment, with an emphasis on fast execution times. The method synthesizes the capabilities of neural network methods for rapid clustering of large partmachine data sets, with multi-objective optimization capabilities of mathematical programming. The procedure includes three phases. In Phase I, part families and associated machine types are identified through neural network methods. Phase II involves a prioritization of part families identified, along with adjustments to certain load-related parameters. Phase III involves interactive goal programming for regrouping machines and labour into cells. In machine grouping, factors such as capacity constraints, cell size restrictions, minimization of load imbalances, minimization of intercell movements of parts, minimization of new ma...
50 citations
TL;DR: In this paper, the Pareto efficiency detection and restoration techniques for integer goal programming are described and the design of the algorithms and their implementation issues within (an otherwise continuous) goal programming system are detailed.
Abstract: This paper focuses on the design, development and implementation of new Pareto efficiency detection and restoration techniques for integer goal programming. The design of the algorithms and their implementation issues within (an otherwise continuous) goal programming system are detailed. The differences between continuous and integer goal programming regarding Pareto efficiency detection and restoration analysis are described. The integer Pareto efficiency techniques have been applied to a selection of problems from different industrial contexts in order to assess their computational performance. Finally, Pareto restoration and detection techniques are applied to an integer goal programming problem to illustrate the methodology.
50 citations
Journal Article•
TL;DR: This paper proposes using a multiple objective linear programming (MOLP) approach for generating a common set of weights in the DEA framework to deal with the difficulty of assessing all the DMUs on the same scale.
Abstract: A characteristic of data envelopment analysis (DEA) is to allow individual decision making units (DMUs) to select the most advantageous weights in calculating their efficiency scores. This flexibility, on the other hand, deters the comparison among DMUs on a common base. For dealing with this difficulty and assessing all the DMUs on the same scale, this paper proposes using a multiple objective linear programming (MOLP) approach for generating a common set of weights in the DEA framework.
50 citations
TL;DR: In this paper, a bilinear goal programming model is developed to achieve the company's objectives, where the complicating binary variables affect the values of the deviational variables of goals attainment, which leads to formulate the master and the sub-problem as two goal programming models with different objective function decompositions as compared to the classical Benders one.
50 citations