RNs and ANs presented a higher risk of reported asthma than administrative staff. The highest risk was associated with tasks involving dilution of disinfection products by manual mixing, suggesting possible exposure to repeated peaks of concentrated products known to be strong respiratory irritants. Workplace interventions should be conducted to more clearly determine QAC exposure and improve disinfection procedures.

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The Job Shop Scheduling Problem (JSP) is an example of a combinatorial optimization problem that has interested researchers for several decades. In this paper we confront an extension of this problem called JSP with Sequence Dependent Setup Times (SDST-JSP). The approach extends a genetic algorithm and a local search method that demonstrated to be efficient in solving the JSP. For local search, we have formalized neighborhood structures that generalize three well-know structures defined for the JSP. We have conducted an experimental study across conventional benchmark instances showing that the genetic algorithm exploited in combination with the local search, considering all three neighborhoods at the same time, provides the best results. Moreover, this approach outperforms the current state-ofthe-art methods.

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This paper tackles the flexible job-shop scheduling problem with uncertain processing times. The uncertainty in processing times is represented by means of fuzzy numbers, hence the name fuzzy flexible job-shop scheduling. We propose an effective genetic algorithm hybridised with tabu search and heuristic seeding to minimise the total time needed to complete all jobs, known as makespan. To build a high-quality and diverse set of initial solutions we introduce a heuristic method which benefits from the flexible nature of the problem. This initial population will be the starting point for the genetic algorithm, which then applies tabu search to every generated chromosome. The tabu search algorithm relies on a neighbourhood structure that is proposed and analysed in this paper; in particular, some interesting properties are proved, such as feasibility and connectivity. Additionally, we incorporate a filtering mechanism to reduce the neighbourhood size and a method that allows to speed-up the evaluation of new chromosomes. To assess the performance of the resulting method and compare it with the state-of-the-art, we present an extensive computational study on a benchmark with 205 instances, considering both deterministic and fuzzy instances to enhance the significance of the study. The results of these experiments clearly show that not only does the hybrid algorithm benefit from the synergy among its components but it is also quite competitive with the state-of-the-art when solving both crisp and fuzzy instances, providing new best-known solutions for a number of these test instances. Genetic Tabu AbstractThis paper tackles the flexible job-shop scheduling problem with uncertain processing times. The uncertainty in processing times is represented by means of fuzzy numbers, hence the name fuzzy flexible job-shop scheduling. We propose an effective genetic algorithm hybridised with tabu search and heuristic seeding to minimise the total time needed to complete all jobs, known as makespan. To build a high-quality and diverse set of initial solutions we introduce a heuristic method which benefits from the flexible nature of the problem. This initial population will be the starting point for the genetic algorithm, which then applies tabu search to every generated chromosome. The tabu search algorithm relies on a neighbourhood structure that is proposed and analysed in this paper; in particular, some interesting properties are proved, such as feasibility and connectivity. Additionally, we incorporate a filtering mechanism to reduce the neighbourhood size and a method that allows to speed-up the evaluation of new chromosomes. To assess the performance of the resulting method and compare it with the state-of-the-art, we present an extensive computational study on a benchmark with 205 instances, considering both deterministic and fuzzy instances to enhance the significance of the study. The results of these experiments clearly show that not only does the hybrid algorithm benefit from the synergy among its component...

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Previous work carried out for the last eight years resulted in the proposal of a complete system of dimensionless groups in order to represent the performance of dierent kinematic Stirling engine con®gurations. When looking for experimental support for the proposed model, some differences between the performances of several prototypes were observed. In this paper an equation is introduced to be applied to all known kinematic engines and to their whole range of performance. The coecients appearing in this equation can be computed from temperature and geometrical dimensionless ratios and from experimental measurements at the maximum indicated power operating point. The meaning of those coecients is interpreted and their usefulness to provide an engine performance overview is shown. The quasi-static simulation and the characteristic Mach number at the maximum indicated power operating point appear to be interesting criteria in order to evaluate the performance of prototypes. NOTATION a, b dimensionless coecients of the friction factor A xx cross-sectional area (m 2 ) C f friction factor L length (m) n s engine speed (r/s) N B Beale number N MA characteristic Mach number n s V 1a3 E a RT C p N p characteristic pressure number p m V 1a3 E a " RT C p N SG N MA N re local instantaneous Reynolds number N RE characteristic Reynolds number p m V 2a3 E n s a "RT C N SG N 2 MA N SG characteristic Stirling number p m a"n s N TCR characteristic regenerator thermal capacity number & r c r T C ap m N W West number N characteristic regenerator thermal diusivity number r aV 1a3 E RT C p p m mean pressure (Pa) P B brake power (W) P ind indicated power (W) r crank radius (m) r hx hydraulic radius (m) R speci®c gas constant (J/kg K) T temperature (K) u local instantaneous¯uid velocity (m/s) V swept volume (m 3 ) V dx dead volume (m 3 ), Y 1 dimensionless coecients of the mechanical losses of the indicated power r regenerator material thermal diusivity (m 2 /s) xx dimensionless cross-sectional area parameter A xx raV E adiabatic coecient 1 , F F F , n angles and other dimensionless parameters of the drive mechanism, normalized by the crank radius dimensionless indicated power P ind ap m V E n s B dimensionless brake power P B ap m V E n s mec dimensionless mechanical losses of the indicated power À B ÁP ind ap m V E n s mec mechanical eciency B a swept volume ratio V C aV E ! dimensionless parameter as de®ned in text ! hx dimensionless hydraulic radius parameter r hx ar heThe MS was