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This paper aims to present a new physically inspired meta-heuristic algorithm, which is called Plasma Generation Optimization (PGO). To evaluate the performance and capability of the proposed method in comparison to other optimization methods, two sets of test problems consisting of 13 constrained benchmark functions and 6 benchmark trusses are investigated numerically. The results indicate that the performance of the proposed method is competitive with other considered state-of-the-art optimization methods.

In this paper, a new physically-based metaheuristic algorithm called plasma generation optimization (PGO) algorithm is developed for solving constrained optimization problems. PGO is a population-based optimizer inspired by the process of plasma generation. In the proposed algorithm, each agent is considered as an electron. Movement of electrons and changing their energy levels are based on simulating excitation, de-excitation and ionization processes occurring through the plasma generation. In the proposed PGO, the global optimum is obtained when plasma is generated with the highest degree of ionization.

A new physically-based metaheuristic algorithm called the PGO algorithm is developed that is inspired from the process of plasma generation.

The results indicate that the performance of the proposed method is competitive with other state-of-the-art methods.

Present study aims to extend the lattice Boltzmann method (LBM) to simulate radiation in geometries with curved boundaries, as the first step to simulate radiation in complex porous media. In recent years, researchers have increasingly explored the use of porous media to improve the heat transfer processes. The lattice Boltzmann method (LBM) is one of the most effective techniques for simulating heat transfer in such media. However, the application of the LBM to study radiation in complex geometries that contain curved boundaries, as found in many porous media, has been limited.

The numerical evaluation of the effect of the radiation-conduction parameter and extinction coefficient on temperature and incident radiation distributions demonstrates that the proposed LBM algorithm provides highly accurate results across all cases, compared to those found in the literature or those obtained using the finite volume method (FVM) with the discrete ordinates method (DOM) for radiative information.

For the case with a conduction-radiation parameter equal to 0.01, the maximum relative error is 1.9% in predicting temperature along vertical central line. The accuracy improves with an increase in the conduction-radiation parameter. Furthermore, the comparison between computational performances of two approaches reveals that the LBM-LBM approach performs significantly faster than the FVM-DOM solver.

The difficulty of radiative modeling in combined problems involving irregular boundaries has led to alternative approaches that generally increase the computational expense to obtain necessary radiative details. To address the limitations of existing methods, this study presents a new approach involving a coupled lattice Boltzmann and first-order blocked-off technique to efficiently model conductive-radiative heat transfer in complex geometries with participating media. This algorithm has been developed using the parallel lattice Boltzmann solver.

This study explores the impact of the residents' voice and social media brand engagement on coopetition in tourism destinations with the mediating role of knowledge sharing. The study's statistical population includes tourists who visited Iran. The sample was 243 tourists who visited Iranian tourist different villages in the spring of 2023. This empirical study adopted a descriptive correlational method and used PLS3 for data analysis. The effects of residents' voices, knowledge sharing, and engagement with social media improve cooperation between tourism destinations, help create platforms for creativity and innovation in this industry, and ensure the promotion of sustainability and attractiveness of tourism. Therefore, the mutual analysis of the effects of different factors in rural tourism in Iran is valuable in providing a new method to improve the tourism experience in this field.

This concluding chapter examines the footprint of coopetition within the tourism domain, drawing upon existing literature to present a comprehensive overview of its evolution to date. To achieve this, the authors conducted a literature review of 94 articles published on coopetition in tourism and hospitality, sourced from esteemed databases such as Scopus and Web of Science. Each article was meticulously categorised based on its thematic focus, geographical scope and the sample of respondents employed to elucidate the dynamics of coopetition. The findings underscore the concerted efforts of researchers to delineate the contours of coopetition within the tourism and hospitality sectors. Through diverse lenses and methodologies, these studies collectively contribute to the burgeoning discourse surrounding coopetition, illuminating its multifaceted implications and applications in different contexts. This chapter presents a systematic analysis that serves as a testament to the growing momentum behind the coopetition paradigm in tourism. It shows how researchers on coopetition are paving the road towards the coopetition paradigm in tourism and hospitality.

Project portfolio management (PPM) is a commonly used technique to align projects with strategy and to ensure adequate resourcing for projects. In this paper, to gain a better understanding of PPM dynamics, a system dynamics (SD) model was developed. To do so, an Iranian independent power producer was used as a case study in the energy sector; moreover, policy options were derived and generalized for such a developer company.

To cope with the complexity of business processes in a power producer company and to formulate an optimum policy, causal relations and loops were derived first and then state-flow diagrams were designed to simulate the problem in the system, as it is usual in the SD methodology.

The proposed model was applied to a real-world case study to rectify managers’ viewpoint about their business dynamics and to formulate new project portfolio strategies to improve the viability of the company. The model proved how a static portfolio analysis can misguide managers in planning their project portfolio strategies, and how effective feedback can improve PPM in developing companies in the energy sector.

Systems approach, especially SD methodology, has been rarely used to analyze PPM problems in the energy sector. This study highlights the implications of feedback and dynamics in PPM and tries to derive optimal value of portfolios.

Nowadays, the risk assessment and reliability engineering of various production processes have become an inevitable necessity. Because if these risks are not going to be evaluated and no solution is going to be taken for their prevention, managing them would be really hard and costly in case of their occurrence. The importance of this issue is much higher in producing healthcare products due to their quality's direct impact on the health of individuals and society.

One of the most common approaches of risk assessment is the failure mode and effects analysis (FMEA), which is facing some limitations in practice. In this research, a new generalized multi-attribute failure mode analysis approach has been proposed by utilizing the best–worst method and linguistic 2-tuple representation in order to evaluate the production process of hemodialysis solution in a case of Tehran, Iran.

According to the results, entry of waste to the mixing tanker, impurity of raw materials and ingredients and fracture of the mixer screw have been identified as the most important potential failures. At last, the results of this research have been compared with the previous studies.

Some reinforcement attributes have been added to the traditional FMEA attributes in order to improve the results. Also, the problems of identical weights for attributes, inaccuracy in experts' opinions and the uncertainties in prioritizing the potential failures were improved. Furthermore, in addition to the need for less comparative data, the proposed approach is more accurate and comprehensive in its results.

In this article, a practical design methodology is proposed for discrete sizing optimization of high-rise concrete buildings with a focus on large-scale and real-life structures.

This framework relies on a computationally efficient approximation of the constraint and objective functions using a radial basis function model with a linear tail, also called the combined response surface methodology (RSM) in this article. Considering both the code-stipulated constraints and other construction requirements, three sub-optimization problems were constructed based on the relaxation model of the original problem, and then the structural weight could be automatically minimized under multiple constraints and loading scenarios. After modulization, the obtained results could meet the discretization requirements. By integrating the commercially available ETABS, a dedicated optimization software program with an independent interface was developed and details for practical software development were also presented in this paper.

The proposed framework was used to optimize different high-rise concrete buildings, and case studies showed that material usage could be saved by up to 12.8% compared to the conventional design, and the over-limit constraints could be adjusted, which proved the feasibility and effectiveness.

This methodology can therefore be applied by engineers to explore the optimal distribution of dimensions for high-rise buildings and to reduce material usage for a more sustainable design.

Diet is recognized as a possible potential factor in migraine pathogenesis. Limited evidence exists on the effect of diet on pediatric migraine, so this paper aims to investigate the association between fruit and vegetable consumption and odds of migraine in children.

The authors conducted a case-control study in tertiary Sina hospital, Tehran, Iran. A hundred children with migraine as case group and 190 sex-matched healthy controls were included in this study. Definite diagnosis of migraine was based on 2018 international classification of headache disorder 3 (ICHD3) criteria. Demographic and anthropometric characteristics were collected. Common dietary intake of participants was obtained using a validated semi-quantitative food frequency questionnaire.

Children in the migraine group had significantly higher BMI and age compared with the control group (p-value = <0.01). After adjustment for age, gender, BMI and total energy intake, a significant association between higher intake of vegetables in second tertile (OR: 0.47; CI: 0.24-0.92), fruits in third tertile (OR: 0.31; CI:0.14-0.69) and fiber in fourth quartile (OR:0.28; CI:0.095-0.85) was obtained. Controlling for all confounders in Model 3, the odds of migraine, decreased by 50 per cent and 70 per cent as the consumption of vegetables and fruits increased, in the second tertile of vegetables (p-value = 0.04) and the third tertile of fruits (p-value = <0.01).

The findings confirm a plausible protective role of dietary fruits and vegetables against the risk of migraine in children, which can be attributed to the probable effect of dietary fiber.

This paper aims to create a comprehensive framework for selecting alternative materials in construction projects, integrating building information modeling (BIM) and the particle swarm optimization (PSO) algorithm. Materials comprise 60%–65% of the total project cost, and current methods require significant time and human resources.

A prototype framework is developed that considers multiple criteria to optimize the material selection process, addressing the significant investment of time and resources required in current methods. The study uses surveys and interviews with construction professionals to collect primary data on alternative materials selection.

The results show that integrating BIM and the PSO algorithm improves cost optimization and material selection outcomes.

This comprehensive tool enhances decision-making capabilities and resource utilization, improving project outcomes and resource utilization. It offers a systematic approach to evaluating and selecting materials, making it a valuable resource for construction professionals.

This paper aims to determine the optimum arrangement of a reverse osmosis system in two methods of plug and concentrate recycling.

To compare the optimum conditions of these two methods, a seawater reverse osmosis system was considered to produce fresh water at a rate of 4,000 m3/d for Mahyarkala city, located in north of Iran, for a period of 20 years. Using genetic algorithms and two-objective optimization method, the reverse osmosis system was designed.

The results showed that exergy efficiency in optimum condition for concentrate recycling and plug methods was 82.6 and 92.4 per cent, respectively. The optimizations results showed that concentrate recycling method, despite a 36 per cent reduction in the initial cost and a 2 per cent increase in maintenance expenses, provides 6 per cent higher recovery and 19.7 per cent less permeate concentration than two-stage plug method.

Optimization parameters include feed water pressure, the rate of water return from the brine for concentrate recycling system, type of SW membrane, feedwater flow rate and numbers of elements in each pressure vessel (PV). These parameters were also compared to each other in terms of recovery (R) and freshwater unit production cost. In addition, the exergy of all elements was analyzed by selecting the optimal mode of each system.