In the recent paper Castro and Doyle (2004) have proposed the Pulp Mill benchmark model, having the standard architecture with a Kamyr digester, a bleaching plant and a chemical recovery. Further Mercangöz and Doyle (2008) have performed the optimization of the benchmark model. The optimization is based on the approximation of the steady state values of the economically significant variables by...

Fuzzy decision tree induction algorithms require the fuzzy quantization of the input variables. This paper demonstrates that supervised fuzzy clustering combined with similarity-based rule-simplification algorithms is an effective tool to obtain the fuzzy quantization of the input variables, so the synergistic combination of supervised fuzzy clustering and fuzzy decision tree induction can be e...

Models for decision-making under uncertainty use probability distributions to represent variables whose values are unknown when the decisions are to be made. Often the distributions are estimated with observed data. Sometimes these variables depend on the decisions but the dependence is ignored in the decision maker’s model, that is, the decision maker models these variables as having an exogen...

The concept of probabilistic argumentation systems PAS is restricted to two types of variables: assumptions, which model the uncertain part of the knowledge, and propositions, which model the rest of the information. Instantiations of PAS have been used for dealing with problems in different contexts. Here, we introduce a third kind of variables into PAS: so-called decision variables. This new ...

T are many critical concerns (including the accounting for endogeneity) when one is properly estimating response functions. However, it is sometimes (certainly not always) better to leave some variables exogenous when building mathematical models intended to help decision makers. The exogenous variables allow the decision maker to better adapt the mathematical model to different situations and ...

This paper describes a new web-based graphical tool “What-If Analyzer for Decision Modeling” that supports what-analysis of different business decision models created in accordance with the DMN standard. It allows a user to modify the decision model by activating/deactivating business rules that represent its decision logic, and immediately see changes in the decision variables. With a simple c...

In this paper, a fuzzy random minimum cost flow problem is presented. In this problem, cost parameters and decision variables are fuzzy random variables and fuzzy numbers respectively. The object of the problem is to find optimal flows of a capacitated network. Then, two algorithms are developed to solve the problem based on Er-expected value of fuzzy random variables and chance-constrained pro...

The paper consists of two parts. The rst one is a concise introduction to epistemic (both propositional and predicate) logic with common knowl-ege operator. As the full common knowledge predicate logics are not even recursively enumerable, in the second part we introduce and investigate the monodic fragment of these logics which allows applications of the epistemic operators to formulas with at...

Let z = (z1, z2, · · · , zn) be noncommutative free variables and t a formal parameter which commutes with z. Let k be a unital commutative ring of any characteristic and Ft(z) = z−Ht(z) with Ht(z) ∈ k[[t]]〈〈z〉〉 ×n and o(Ht(z)) ≥ 2. Note that Ft(z) can be viewed as a deformation of the formal map F (z) := z−Ht=1(z) when it makes sense. The inverse map Gt(z) of Ft(z) can always be written as Gt(...

In this paper we prove decidability of two kinds of branching time temporal logics. First we show that the non-local version of propositional , in which truth values of atoms may depend on the branch of evaluation, is decidable. Then we use this result to establish decidability of various fragments of quantified , where the next-time operator can be applied only to formulas with at most one fre...