Resum The volume and availability of business and finance data may continue to increase in the near future. However, the utility of such data is by no means straightforward due to a lack of integration between data-driven techniques and usual decision-making processes. This paper aims to integrate data with multiobjective decision-making in cash management by means of machine learning. To this ...

D ecision-making for planning a petrochemical industry is a difficult task, particularly when decisions are required to be made under constraints and different objectives. This paper presents the application of multiobjective optimization tools for planning of a mixed-integer model of a petrochemical industry to arrive at a small set of good solutions out of the Pareto optimal solutions. The tw...

Resum The volume and availability of business and finance data may continue to increase in the near future. However, the utility of such data is by no means straightforward due to a lack of integration between data-driven techniques and usual decision-making processes. This paper aims to integrate data with multiobjective decision-making in cash management by means of machine learning. To this ...

The paper presents a multiobjective optimization approach to process parameter optimization in continuous casting of steel, which is the most widely used steel production process. The optimization task is to find parameter values such that the target values of the empirical metallurgical optimization criteria are approached as closely as possible, since this in turn results in high quality of t...

We introduce a novel approximation method for multiobjective optimization problems called PAINT–SiCon. The method can construct consistent parametric representations of Pareto sets, especially for nonconvex problems, by interpolating between nondominated solutions of a given sampling both in the decision and objective space. The proposed method is especially advantageous in computationally expe...

Resum The volume and availability of business and finance data may continue to increase in the near future. However, the utility of such data is by no means straightforward due to a lack of integration between data-driven techniques and usual decision-making processes. This paper aims to integrate data with multiobjective decision-making in cash management by means of machine learning. To this ...

is paper presents a new procedure to solve multiobjective problems, where the objectives are distributed to various working groups and the decision process is centralized. e approach is interactive and considers the preferences of the working groups. It is based on two techniques: an interactive technique that solves multi-objective problems based on goal programming, and a technique called “...

Resum The volume and availability of business and finance data may continue to increase in the near future. However, the utility of such data is by no means straightforward due to a lack of integration between data-driven techniques and usual decision-making processes. This paper aims to integrate data with multiobjective decision-making in cash management by means of machine learning. To this ...

tAuthor to whom all correspondence should be addressed. :~Reseaxch of these authors was supported by the CNPq Grant No. 550408-2002/9. 0898-1221/06/$ see front matter (~) 2006 Elsevier Ltd. All rights reserved. doi:10.1016/j.camwa.2006.08.012 Typeset by A A~-TEX 180 P. YA. EKEL et al. Ueywords -Unce r t a in ty factor, Fuzzy coefficients, Interrelated models, Multiobjective decision making, Fuz...

Resum The volume and availability of business and finance data may continue to increase in the near future. However, the utility of such data is by no means straightforward due to a lack of integration between data-driven techniques and usual decision-making processes. This paper aims to integrate data with multiobjective decision-making in cash management by means of machine learning. To this ...