in this paper, a multi-objective method is used to optimize a heat recovery steam generator (hrsg). two objective functions have been used in the optimization, which are irreversibility and hrsg equivalent volume. the former expresses the exergetic efficiency and the latter demonstrates the cost of the hrsg. decision variables are geometric and operational parameters of the hrsg. the results of...

A crucial characteristic of machine learning models in various domains (such as medical diagnosis, financial analysis, or real-time process monitoring) is the interpretability. The interpretation supports humans understanding meaning behind every single prediction made by machine, and enables user to assess trustworthiness before acting on predictions. This article presents our work building an...

In this paper, a quadratic programming (FFQP) problem is considered in which all of the cost coefficients, constraints coefficients, and right hand side of the constraints are characterized by L-R fuzzy numbers. Through this paper, the concept of α- level of fuzzy numbers for the objective function, and the order relations on the fuzzy numbers for the constraints are considered.  To optimize th...

In practical optimization, a priority requirement for different objectives of multiple objective optimization problems should be considered. In this paper, the distributed power management of a Virtual Power Plant (VPP) with priority requirement is optimized by the compromised method. The operation optimization model of VPP is formulated as a fuzzy multiple objective optimization problem consid...

Multiple sequence alignment is a fundamental problem in computational molecular biology. This paper shows a brand new refinement strategy combining divide-and-conquer and Beam-Through alignment (DC-BTA). Optimization objective function (OF) is additively computed with new stage beam area, which is corresponding to beam area rate in [6]. The refinement is based on previous alignment result to ex...

This report documents the program and outcomes of the Dagstuhl Seminar 15031 Understanding Complexity in Multiobjective Optimization. This seminar carried on the series of four previous Dagstuhl Seminars (04461, 06501, 09041 and 12041) that were focused on Multiobjective Optimization, and strengthening the links between the Evolutionary Multiobjective Optimization (EMO) and Multiple Criteria De...