Abstract
A significant number of search and optimisation techniques whose principles seek inspiration from nature and biology phenomena have been proposed in the last decades. These methods have been successfully applied to solve a wide range of engineering problems. This is also the case of greenhouse environment control, which has been incorporating this type of techniques into its design. This paper addresses evolutionary and bio-inspired methods in the context of greenhouse environment control. Algorithm principles for reference techniques are reviewed, namely: simulated annealing, genetic algorithm, differential evolution and particle swarm optimisation. The last three techniques are considered using single and multiple objective formulations. A review of these algorithms within greenhouse environment control applications is presented, considering single and multiple objective problems, as well as their current trends.

Abstract
The transport of patients from the inpatient service to the operating room is a recurrent task in the hospital routine. This task is repetitive, non-ergonomic, time consuming, and requires the labor of patient transporters. In this paper is presented the design of a driverless wheelchair under development capable of providing an on-demand mobility service to hospitals. The proposed wheelchair can receive transportation requests directly from the hospital information management system, pick-up patients at their beds, navigate autonomously through different floors, avoid obstacles, communicate with elevators, and drop patients off at the designated destination.

Abstract
This paper addresses a two-dimensional (2D) non-guillotine cutting problem, where a set of small rectangular items of given types has to be cut from a large rectangular stock plate having defective regions so as to maximize the total value of the rectangles cut. The number of small items of each item type which can be cut from the large object is unrestricted. A novel MIP model and a hybrid approach combining a novel placement procedure with a biased random-key genetic algorithm (BRKGA) are presented. The parameters used by the novel placement procedure for the development of a cutting plan are evolved by the BRKGA. The management of the free spaces and of the defects uses a maximal-space representation. The approach is evaluated and compared to other approaches by means of a series of detailed numerical experiments using 5414 benchmark instances taken from the literature. The experimental results validate the quality of the solutions and the effectiveness of the proposed algorithm.

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Abstract
Purpose The purpose of this paper is to research the way in which Lean practices are affecting the performance of manufacturing small and medium enterprises (SMEs), analyzing the effects of Lean practices on companies' operational, financial and market performance. Design/methodology/approach An online questionnaire was distributed among Portuguese organizations that fitted the category of SMEs and belonged to the manufacturing sector. A sample of 329 enterprises was analyzed with partial least squares-structural equation modelling. Four hypotheses on the impact of Lean practices on company performance were tested. Findings The results show that the effects of Lean on performance are positive, which stresses the benefits attainable with the implementation of Lean practices. The aggregated implementation of Lean practices, namely, customer involvement, statistical process, continuous flow and total productive maintenance leads to improvements in company's global performance measured by market, financial and operational performance measures, and also improves each of these performance measures individually. It was also noticed that financial capability is one of the indispensable factors for the successful implementation of Lean practices. Originality/value This is the first study that examines the impact of the effect of Lean on operational, financial and market performance in a discriminated and simultaneous way.

Abstract
Background: The estimation of the real number of COVID-19 infected people is one of the concerns of the governments around the world. In this sense, this study seeks to assess the incidence and fatality of COVID-19 in Europe considering the expected number of the infected cases. Methods: A quantitative exploratory study was performed on the top 10 countries most affected by COVID-19 by 9th June in Europe. Furthermore, this study presents three propagation estimation models of the COVID-19 that help us to understand the real incidence of the pandemic in each country. Each model is briefly explained and applied. Results: The findings revealed a great heterogeneity of COVID-19 cases and deaths among the countries. The indicator of the number of deaths reveals the greatest disparity between other countries with the United Kingdom, recording about 6 or 7 times more deaths than Russia or Germany. Infection fatality rate (IFR) tends to be a more reliable indicator when analyzing data because it is less dependent on the number of tests performed. Conclusion: Several estimation models can be used to determine the incidence of COVID-19. However, their results in European countries are still quite asymmetrical although they are more reliable than just looking at the perspective of the number of cases or deaths recorded. The infection fatality rate (IFR) emerges as a more accurate indicator by estimating the expected number of registered cases, which includes asymptomatic cases and patients with mild symptoms that are not known and reported by health authorities. © 2020 The authors.