The Promise, Practice, and State of Planning Tools to Assess Site Vulnerability to Runoff Phosphorus Loss

Publication history: Accepted - 23 October 2017; Published online - 1 November 2017.Over the past 20 yr, there has been a proliferation of phosphorus (P) site assessment tools for nutrient management planning, particularly in the United States. The 19 papers that make up this special section on P site assessment include decision support tools ranging from the P Index to fate-and-transport models to weather-forecast-based risk calculators. All require objective evaluation to ensure that they are effective in achieving intended benefits to protecting water quality. In the United States, efforts have been underway to compare, evaluate, and advance an array of P site assessment tools. Efforts to corroborate their performance using water quality monitoring data confirms previously documented discrepancies between different P site assessment tools but also highlights a surprisingly strong performance of many versions of the P Index as a predictor of water quality. At the same time, fate-and-transport models, often considered to be superior in their prediction of hydrology and water quality due to their complexity, reveal limitations when applied to site assessment. Indeed, one consistent theme from recent experience is the need to calibrate highly parameterized models. As P site assessment evolves, so too do routines representing important aspects of P cycling and transport. New classes of P site assessment tools are an opportunity to move P site assessment from general, strategic goals to web-based tools supporting daily, operational decision

Using Dynastic Exploring Recombination to Promote Diversity in Genetic Search

A family of recombination operators is studied in this work. These operators are based on keeping and using certain information about the past evolution of the algorithm to guide the recombination process. Within this framework, several recombination operators are specifically designed to preserve diversity within the population, while avoiding implicit mutations. The empirical evaluation of these operators on instances of two test problems (k-EMP and permutation flowshop) shows an improvement of the results with respect to other classical operators. This improvement seems to related to the increasing degree of epistasis of the problem

Fitness distributions and GA hardness

Considerable research effort has been spent in trying to formulate a good definition of GA-Hardness. Given an instance of a problem, the objective is to estimate the performance of a GA. Despite partial successes current definitions are still unsatisfactory. In this paper we make some steps towards a new, more powerful way of assessing problem difficulty based on the properties of a problem's fitness distribution. We present experimental results that strongly support this idea

Memetic Algorithms for Nurse Rostering

Nurse rostering problems represent a subclass of scheduling problems that are hard to solve. The goal is finding high quality shift and resource assignments, satisfying the needs and requirements of employees as well as the employers in healthcare institutions. In this paper, a real case of a nurse rostering problem is introduced. Memetic Algorithms utilizing different type of promising genetic operators and a self adaptive violation directed hierarchical hill climbing method are presented based on a previously proposed framework