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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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TL;DR: A conceptual framework is proposed to help the decision maker in choosing the most appropriate methodology in the evaluation process, and a new model, called GAHP, is offered for the evaluation problem combining integer goal linear programming and Analytic Hierarchy Process in a single hybrid multiple objective multi-criteria model.
Abstract: The decision to acquire a new information technology poses a number of serious evaluation and selection problems to technology managers, because the new system must not only meet current information requirements of the organisation, but also the needs for future expansion. Tangible and intangible benefits factors, as well as risks factors, must be identified and evaluated. The paper provides a review of ten major evaluation categories and available models, which fall under each category, showing their advantages and disadvantages in handling the above difficulties. This paper describes strategic implications involved in the selection decision, and the inherent difficulties in: (1) choosing or developing a model, (2) obtaining realistic inputs for the model, and (3) making tradeoffs among the conflicting factors. It proposes a conceptual framework to help the decision maker in choosing the most appropriate methodology in the evaluation process. It also offers a new model, called GAHP, for the evaluation problem combining integer goal linear programming and Analytic Hierarchy Process (AHP) in a single hybrid multiple objective multi-criteria model. A goal programming methodology, with zero-one integer variables and mixed integer constraints, is used to set goal target values against which information technology alternatives are evaluated and selected. AHP is used to structure the evaluation process providing pairwise comparison mechanisms to quantify subjective, nonmonetary, intangible benefits and risks factors, in deriving data for the model. A case illustration is provided showing how GAHP can be formulated and solved.

51 citations

Journal ArticleDOI
TL;DR: In this article, the authors proposed a nonlinear programming model for the internal due date assignment in a wafer fab to predict the completion time and cycle time of all the jobs in the fab.
Abstract: To enhance the performance of the internal due date assignment in a wafer fab even further, this study incorporated the fuzzy c-means-back propagation network (FCM-BPN) approach with a nonlinear programming model. In the proposed methodology, the jobs are first classified into several categories by fuzzy c-means. Then, an individual back propagation network is constructed for each category to predict the completion time of the jobs. Subsequently, an individual nonlinear programming model is constructed for each back propagation network to adjust the connection weights in the back propagation network, allowing us to determine the internal due dates of the jobs in the category. The nonlinear programming model is finally converted into a goal programming problem that can be solved with existing optimization software. According to the experimental results, the proposed methodology outperforms the baseline multiple linear regression (MLR) approach by 24% in predicting the job completion/cycle times. In addition, the proposed methodology also guarantees that all jobs can be finished before the established internal due dates, without adding too large a fudge factor, and without sacrificing the accuracy of the completion/cycle time forecasts.

51 citations

Journal ArticleDOI
TL;DR: This paper develops a general formulation of dependent-chance goal programming (DCGP) which is an extension of stochastic goal programming in a complex Stochastic system, and gives an example of water allocation and supply to show the application of DCGP.

50 citations

Journal ArticleDOI
TL;DR: A unique integrated multi-attribute decision making (MADM) and mathematical programming (MP)-based model in a mixed environment by combining decision making trial and evaluation laboratory (DEMATEL)-based on analytic network process (ANP), i.e., DANP, fuzzy technique for order of preference by similarity to ideal solution.

50 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
202335
202271
2021151
2020138
2019160
2018145