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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06 Jul 1999
TL;DR: This paper poses the goal programming problem as a multi-objective optimization problem of minimizing deviations from individual goals and suggests that the proposed approach is a unique, effective, and practical tool for solving goal programming problems.
Abstract: Goal programming is a technique often used in engineering design activities primarily to find a compromised solution which will simultaneously satisfy a number of design goals. In solving goal programming problems, classical methods reduce the multiple goal-attainment problem into a single objective of minimizing a weighted sum of deviations from goals. In this paper, we pose the goal programming problem as a multi-objective optimization problem of minimizing deviations from individual goals. This procedure eliminates the need of having extra constraints needed with classical formulations and also eliminates the need of any user-defined weight factor for each goal. The proposed technique can also solve goal programming problems having a non-convex trade-off region, which are difficult to solve using classical methods. The efficacy of the proposed method is demonstrated by solving a number of test problems and by solving an engineering design problem. The results suggest that the proposed approach is a unique, effective, and practical tool for solving goal programming problems.
99 citations
TL;DR: It is shown that, in the case that one of the goals is fully achieved, a fuzzy-efficient solution may not be Pareto-optimal and therefore a general procedure to obtain a non-dominated solution, which is also fuzzy- efficient is proposed.
99 citations
TL;DR: The proposed model accomplishes forecasting adjustments, material management, and production activities, and Zimmermann's fuzzy programming method is applied for achieving an overall satisfactory compromise solution.
98 citations
TL;DR: A multiple objective advanced remanufacturing- to-order and disassembly-to-order (ARTODTO) system is proposed as an order-driven component and product recovery (ODCPR) system to achieve multiple conflicting financial, environmental and quality-based goals.
98 citations
TL;DR: The integer linear goal-programming technique is used to determine optimal criterion weights which minimize the number of misclassification of decisions, and the hit ratio is compared.
Abstract: In repetitive judgmental discrete decision-making with multiple criteria, the decision maker usually behaves as if there is a set of appropriate criterion weights such that the decisions chosen are based on the weighted sum of all the criteria. Many different procedures for estimating these implied criterion weights have been proposed. Most of these procedures emphasize the preference trade-off among the multiple criteria of the decision maker, and thus the criterion weights obtained are not directly related to the hit ratio of matching decisions. Based on past data, statistical discriminant analysis can be used to determine the implied criterion weights that would reflect the past decisions. The most interesting performance measure is the hit ratio. In this work, we use the integer linear goal-programming technique to determine optimal criterion weights which minimize the number of misclassification of decisions. The linear goal-programming formulation has m constraints and m + k + 1 variables, where m is the number of cases and k is the number of criteria. Empirical study is done by using two different procedures on the actual past admission data of an M.B.A. programme. The hit ratios of the different procedures are compared.
98 citations