Abstract
One major practical problem when applying traditional metaheuristics seems to be their strong dependency on parameter tuning. This issue is frequently pointed out as a major shortcoming of metaheuristics and is often a reason for Decision-Makers to reject using this type of approach in practical situations. In this paper we present a new search strategy - Constraint Oriented Neighbourhoods - that tries to overcome the referred drawback. The aim is to control the grade of randomness of metaheuristics, by defining "special" neighbourhood movements, that lead to a more robust heuristic, less dependent on parameter tuning. This is achieved by selecting and applying particular movements that take into account the potential violation of problem constraints. The strategy is illustrated in a real problem arising in the area of Power Systems Management - the Unit Commitment Problem, the computational experiments on a set of problem instances systematically outperforming those presented in the literature, both in terms of efficiency, quality of the solution and robustness of the algorithm.

Abstract
Genetic interventions that accelerate or retard aging in mice are crucial in advancing our knowledge over mammalian aging. Yet determining if a given intervention affects the aging process is not straightforward since, for instance, many disease-causing mutations may decrease life span without affecting aging. In this work, we employed the Gompertz model to determine whether several published interventions previously claimed to affect aging in mice do indeed alter the aging process. First, we constructed age-specific mortality tables for a number of mouse cohorts used in longevity experiments and calculated the rate at which mortality increases with age. Estimates of age-independent mortality were also calculated. We found no statistical evidence that GHRHR, IGF1R, INSR, PROP1, or TRX delay or that ATM + TERC, BubR1, klotho, LMNA, PRDX1, p53, WRN + TERC, or TOP3B accelerate mouse aging. Often, changes in the expression of these genes affected age-independent mortality and so they may prove useful to other aspects of medicine. We found statistical evidence that C/EBP, MSRA, SHC1, growth hormone, GHR, PIT1, and PolgA may influence aging in mice. These results were interpreted together with age-related physiological and pathological changes and provide novel insights regarding the role of several genes in the mammalian aging process.

Abstract

Abstract
This paper develops a framework for performance appraisal in the context of a bank branch network. A data envelopment analysis model is advocated that can identify both input and output inefficiencies from a cost minimization perspective. The model is then applied to the analysis of a bank branch network and the production and value-added approaches are deployed jointly to give a comprehensive assessment of bank branch efficiency. The sources of underperformance are identified and their managerial implications are explored.

Abstract
This paper enhances cost efficiency measurement methods to account for different scenarios relating to input price information. These consist of situations where prices are known exactly at each decision making unit (DMU) and situations with incomplete price information. The main contribution of this paper consists of the development of a method for the estimation of upper and lower bounds for the cost efficiency (CE) measure in situations of price uncertainty, where only the maximal and minimal bounds of input prices can be estimated for each DMU. The bounds of the CE measure are obtained from assessments in the light of the most favourable price scenario (optimistic perspective) and the least favourable price scenario (pessimistic perspective). The assessments under price uncertainty are based on extensions to the Data Envelopment Analysis (DEA) model that incorporate weight restrictions of the form of input cone assurance regions. The applicability of the models developed is illustrated in the context of the analysis of bank branch performance. The results obtained in the case study showed that the DEA models can provide robust estimates of cost efficiency even in situations of price uncertainty.

Abstract
Markov models have been widely used for modelling users' web navigation behaviour. In previous work we have presented a dynamic clustering-based Markov model that accurately represents second-order transition probabilities given by a collection of navigation sessions. Herein, we propose a generalisation of the method that takes into account higher-order conditional probabilities. The method makes use of the state cloning concept together with a clustering technique to separate the navigation paths that reveal differences in the conditional probabilities. We report on experiments conducted with three real world data sets. The results show that some pages require a long history to understand the users choice of link, while others require only a short history. We also show that the number of additional states induced by the method can be controlled through a probability threshold parameter.