Synthesis of refrigeration system based on generalized disjunctive programming model

Refrigeration system holds an important role in process industries. The optimal synthesis cannot only reduce the energy consumption, but also save the production costs. In this study, a general methodology is developed for the optimal design of refrigeration cycle and heat exchanger network(HEN) simultaneously. Taking the heat integration between the external heat sources/sinks and the refrigeration cycle into consideration, a superstructure with sub-coolers is developed. Through defining logical variables that indicate the relative temperature positions of refrigerant streams after sub-coolers, the synthesis is formulated as a Generalized Disjunctive Programming(GDP) problem based on LP transshipment model, with the target of minimizing the total compressor shaft work in the refrigeration system. The GDP model is then reformulated as a Mixed Integer Nonlinear Programming(MINLP) problem with the aid of binary variables and Big-M Constraint Method. The efficacy of the process synthesis model is demonstrated by a case study of ethylene refrigeration system. The result shows that the optimization can significantly reduce the exergy loss as well as the total compression shaft work.

An Approach for Handling Conflicts in Authorization

Based on logic programs, authorization conflicts and resolution strategies are analyzed through the explanation of some examples on the health care sector. A resolution scheme for handling conflicts in high level authorization specification by using logic program with ordered disjunction （LPOD） is proposed. The scheme is useful for solving conflicts resulted from combining positive and negative authorization, complexity of authorization management, and less clarity of the specification. It can well specify kinds of conflicts （such as exceptional conflicts, potential conflicts）, and is based on literals and dependent contexts. Thus it is expressive and available. It is shown that authorizations based on rules LPOD is very important both in theory and practice.

Comparison of Semantics of Disjunctive Logic Programs Based on Model-Equivalent Reduction

In this paper, it is shown that stable model semantics, perfect model semantics, and partial stable model semantics of disjunctive logic programs have the same expressive power with respect to the polynomial-time model-equivalent reduction. That is, taking perfect model semantics and stable model semantic as an example, any logic program P can be transformed in polynomial time to another logic program P＇ such that perfect models （resp. stable models） of P i-i correspond to stable models （resp. perfect models） of P＇, and the correspondence can be computed also in polynomial time. However, the minimal model semantics has weaker expressiveness than other mentioned semantics, otherwise, the polynomial hierarchy would collapse to NP.

The Least Fixpoint Transformation for Disjunctive Logic Programs

The paradigm of disjunctive logic programming (DLP) enhances greatly the expressive power of normal logic programming (NLP) and many (declarative) semantics have beeu defined for DLP to cope with various problems of knowledge representation in artificial intelligence. However, the expressive ability of the semantics and the soundness of program transformations for DLP have been rarely explored. This paper defines an immediate consequence operator TGP for each disjunctive program and shows that TGP has the least and computable fixpoint Lft(P). Lft is, in fact, a program transformation for DLP which transforms all disjunctive programs into negative programs. It is shown that Lft preserves many key semantics, including the disjunctive stable models, well-founded model, disjunctive argument semantics DAS, three-valued models, etc. This means that every disjunctive program P has a unique canonical form Lft(P) with respect to these semanics. As a result, the work in this paper provides a unifying frameword for studying the expressive ability of various semantics for DLP.On the other hand, the computing of the above semantics for negative programs is just a trivial task, therefore, Lft(P) is also an optimization method for DLP. Another application of Lft is to derive some interesting semantic results for DLP.