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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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Journal ArticleDOI
TL;DR: How generalized goal programming problems can be solved using the Visual Interactive Approach (Korhonen and Laakso, 1986) and how this approach can be implemented using any standard linear optimization package with a parametric optimization routine.

66 citations

Journal ArticleDOI
TL;DR: A goal programming (GP) approach is adopted to solve the SMONDP models and three stochastic GP models with different philosophies are provided to model planners' NDP decision under demand uncertainty, i.e., the expected value GP models, chance-constrained GP model, and dependent-chance GP model.
Abstract: The transportation network design problem (NDP) with multiple objectives and demand uncertainty was originally formulated as a spectrum of stochastic multi-objective programming models in a bi-level programming framework. Solving these stochastic multi-objective NDP (SMONDP) models directly requires generating a family of optimal solutions known as the Pareto-optimal set. For practical implementation, only a good solution that meets the goals of different stakeholders is required. In view of this, we adopt a goal programming (GP) approach to solve the SMONDP models. The GP approach explicitly considers the user-defined goals and priority structure among the multiple objectives in the NDP decision process. Considering different modeling purposes, we provide three stochastic GP models with different philosophies to model planners' NDP decision under demand uncertainty, i.e., the expected value GP model, chance-constrained GP model, and dependent-chance GP model. Meanwhile, a unified simulation-based genetic algorithm (SGA) solution procedure is developed to solve all three stochastic GP models. Numerical examples are also presented to illustrate the practicability of the GP approach in solving the SMONDP models as well as the robustness of the SGA solution procedure.

66 citations

Journal ArticleDOI
TL;DR: In this paper, the authors present an integrated design and marketing approach to facilitate the generation of an optimal robust set of product design alternatives to carry forward to the prototyping stage, considering variability in both (i) engineering design domain, and (ii) customer preferences in marketing domain.
Abstract: We present an integrated design and marketing approach to facilitate the generation of an optimal robust set of product design alternatives to carry forward to the prototyping stage. The approach considers variability in both (i) engineering design domain, and (ii) customer preferences in marketing domain. In the design domain, the approach evaluates performance and robustness of a design alternative due to variations in its uncontrollable parameters. In the marketing domain, in addition to considering competitive product offerings, the approach considers designs that are robust in customer preferences with respect to: (1) the variations in the design domain, and (2) the inherent variations in the estimates of preferences given the fit of the preference model to the sampled data. Our overall goal is to obtain design alternatives that are multi-objectively robust and optimal, i.e., (1) are optimal for nominal values of parameters, and (2) are within a known acceptable range in their multi-objective performance, and (3) maintain feasibility even when they are subject to applications and environments that are different from nominal or standard laboratory conditions. We illustrate the highlights of our approach with the design of a corded power tool example.

66 citations

Journal ArticleDOI
TL;DR: In this paper, a multi-objective mathematical model is proposed to design a sustainable-resilient supply chain based on strategic and tactical decision levels to satisfy customer demands when the firm is highly vulnerable to operational and disruption risks.

66 citations

Journal ArticleDOI
TL;DR: The proposed methodology is based on the combination of discrete and continuous multicriteria decision aid (MCDA) methods for MFs selection and composition and is applied on data of Greek MFs over the period 1999–2001 with encouraging results.

66 citations


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