In a model with ex-ante homogenous households, income risk and a general earnings function, we derive an optimal labor tax rate and optimal education subsidies. It turns out that the distinction of risk-increasing or risk-decreasing education does not have much effect on the optimal tax rate, but is crucial for optimal education subsidies. Moreover, an optimal education policy allows for better...

This paper presents a novel decomposition strategy for solving large scale refinery scheduling problems. Instead of formulating one huge and unsolvable MILP or MINLP for centralized problem, we propose a general decomposition scheme that generates smaller sub-systems that canbe solved toglobal optimality. The original problem is decomposed at intermediate storage tanks such that inlet and outle...

Multi-objective optimization yields multiple solutions each of which is no better or worse than the others when the objectives are conflicting. These solutions lie on the Pareto-optimal front which is a lower-dimensional slice of the objective space. Together, the solutions may possess special properties that make them optimal over other feasible solutions. Innovization is the process of extrac...

Lexicase selection is a parent selection method that considers training cases individually, rather than in aggregate, when performing parent selection. Whereas previous work has demonstrated the ability of lexicase selection to solve difficult problems, the central goal of this paper is to develop the theoretical underpinnings that explain its performance. To this end, we derive an analytical f...

0377-2217/$ see front matter 2009 Elsevier B.V. A doi:10.1016/j.ejor.2009.02.013 * Corresponding author. E-mail address: [email protected] (A. Kus This paper presents a framework for finding optimal modules in a delayed product differentiation scenario. Historical product sales data is utilized to estimate demand probability and customer preferences. Then this information is used by a mul...

In this paper, we focus on expensive multiobjective optimization problems and propose a method to predict an approximation of the Pareto optimal set using classification of sampled decision vectors as dominated or nondominated. The performance of our method, called EPIC, is demonstrated on a set of benchmark problems used in the multiobjective optimization literature and compared with state-of ...

We present a new release of PRISM-games, a tool for verification and strategy synthesis for stochastic games. PRISM-games 2.0 significantly extends its functionality by supporting, for the first time: (i) long-run average (mean-payoff) and ratio reward objectives, e.g., to express energy consumption per time unit; (ii) strategy synthesis and Pareto set computation for multi-objective properties...

A comprehensive thermodynamic study is conducted of a diesel based Combined Heat and Power (CHP) system, based on a diesel engine and an Organic Rankine Cycle (ORC). Present research covers both energy and exergy analyses along with a multiobjective optimization. In order to determine the irreversibilities in each component of the CHP system and assess the system performance, a complete paramet...

We propose an extension of the classical real-valued external penalty method to the multicriteria optimization setting. As its single objective counterpart, it also requires an external penalty function for the constraint set, as well as an exogenous divergent sequence of nonnegative real numbers, the so-called penalty parameters, but, differently from the scalar procedure, the vector-valued me...

China has seen the fruit of its rapid economic growth over the past two decades, but severe environmental problems have accompanied this, such as the looming danger of Asian Brown Clouds. This paper analyzes the regional development of China by examining economic performance as well as environmental factors. Technical efficiency and productivity changes of thirty-one regions in China during the...