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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.

This paper aims to present a new multi-community meta-heuristic optimization algorithm, which is called shuffled shepherd optimization algorithm (SSOA). In this algorithm.

The agents are first separated into multi-communities and the optimization process is then performed mimicking the behavior of a shepherd in nature operating on each community.

A new multi-community meta-heuristic optimization algorithm called a shuffled shepherd optimization algorithm is developed in this paper and applied to some attractive examples.

A new metaheuristic is presented and tested with some classic benchmark problems and some attractive structures are optimized.

In this research, the free vibration sensitivity analysis of cracked fiber metal laminated (FML) beams is investigated numerically and experimentally. The effects of single and double cracks on the frequency of the cantilever beams are simulated using the finite element method (FEM) and compared to the experimental results.

In FEM analysis, the crack defect is simulated by the contour integral technique without considering the crack growth. The specimens are fabricated with an aluminum sheet, woven carbon fiber and epoxy resin. The FML specimens are constructed by bonding five layers as [carbon fiber-epoxy/Al/carbon fiber-epoxy/Al/carbon fiber-epoxy]. First, the location and length of cracks are considered input factors for the frequency sensitivity analysis. Then, the design of the experiment is produced in the cases of single and double cracks to compute the frequency of the beams in the first and second modes using the FEM. The mechanical shaker is used to determine the natural frequency of the specimens. In addition, the predicted response values of the frequency for the beam are used to compare with the experimental results.

Consequently, the results of the sensitivity analysis demonstrate that the location and length of the crack have significant effects on the modes.

Effective interaction diagrams are introduced to investigate crack detection for input factors, including the location and length of cracks in the cases of single and double cracks.

The purpose of this study is to investigate the post-buckling analysis of functionally graded columns by using three analytical, approximate and numerical methods. A pre-defined function as an initial assumption for the post-buckling path is introduced to solve the differential equation. The finite difference method is used to approximate the lateral deflection of the column based on the differential equation. Moreover, the finite element method is used to derive the tangent stiffness matrix of the column.

The non-linear buckling analysis of functionally graded materials is carried out by using three analytical, finite difference and finite element methods. The elastic deformation and Euler-Bernoulli beam theory are considered to establish the constitutive and kinematics relations, respectively. The governing differential equation of the post-buckling problem is derived through the energy method and the calculus variation.

An incremental iterative solution and the perturbation of the displacement vector at the critical buckling point are performed to determine the post-buckling path. The convergence of the finite element results and the effects of geometric and material characteristics on the post-buckling path are investigated.

The key point of the research is to compare three methods and to detect error sources by considering the derivation process of relations. This comparison shows that a non-incremental solution in the analytical and finite difference methods and an initial assumption in the analytical method lead to an error in results. However, the post-buckling path in the finite element method is traced by the updated tangent stiffness matrix in each load step without any initial limitation.

This paper addresses a location-routing problem (LRP) under uncertainty for providing emergency medical services (EMS) during disasters, which is formulated using a robust optimization (RO) approach. The objectives consist of minimizing relief time and the total cost including location costs and the cost of route coverage by the vehicles (ambulances and helicopters).

A shuffled frog leaping algorithm (SFLA) is developed to solve the problem and the performance is assessed using both the ε-constraint method and NSGA-II algorithm. For a more accurate validation of the proposed algorithm, the four indicators of dispersion measure (DM), mean ideal distance (MID), space measure (SM), and the number of Pareto solutions (NPS) are used.

The results obtained indicate the efficiency of the proposed algorithm within a proper computation time compared to the CPLEX solver as an exact method.

In this study, the planning horizon is not considered in the model which can affect the value of parameters such as demand. Moreover, the uncertain nature of the other parameters such as traveling time is not incorporated into the model.

The outcomes of this research are helpful for decision-makers for the planning and management of casualty transportation under uncertain environment. The proposed algorithm can obtain acceptable solutions for real-world cases.

A novel robust mixed-integer linear programming (MILP) model is proposed to formulate the problem as a LRP. To solve the problem, two efficient metaheuristic algorithms were developed to determine the optimal values of objectives and decision variables.

The study sought to examine the impacts of COVID-19 on tourism from the stakeholder perspective in the case of Famagusta town in Northern Cyprus.

Via a qualitative research approach, data are collected through face-to-face interviews from direct and indirect tourism stakeholders operating in Famagusta. A judgmental sampling strategy was employed to collect data from tourism stakeholders on the impacts of COVID-19 on tourism. Descriptive data analysis is engaged to report the results.

Results of the study showed that the novel coronavirus has hampered the tourism sector in Famagusta, Northern Cyprus. Indeed, as the globe suffered its effects in terms of economic gains, business and business closure. It has been the same with Famagusta, while a few private sectors positively gained (Internet and Technology), all other tourism-reliant sectors such as hotels, restaurants, travel agencies and the transport sector massively suffered as a result of the global lockdown due to COVID-19 pandemic.

Given the ever-changing state of knowledge and scarcity of literature, the current study seeks to summarize what has been learned from previous crises and back it up with qualitative research including senior industry stakeholders.

This study aims to build upon resource orchestration theory to theorize and empirically test a model that demonstrates how knowledge assets and innovation ambidexterity trigger a synergy in favor of firm performance.

Drawing on a survey of 158 Iranian knowledge-intensive companies, this study uses the partial least squares based on structural equation modeling to test the research hypotheses.

The results show that two elements of knowledge assets, namely, structural and relational capital, indirectly affect firm performance through the full mediation of innovation ambidexterity. The findings indicate that human capital has no relationship with both innovation ambidexterity and firm performance.

This study offers fresh insights into the issue of how organizations can create value from an effective orchestration of various strategic resources and capabilities, including knowledge assets and innovation ambidexterity.

This study applies resource orchestration theory to concurrently the areas of knowledge resources and organizational ambidexterity to show how innovation ambidexterity plays a role in translating three various knowledge assets into performance.

The increasing prevalence of coronavirus disease (COVID-19) is a global crisis that leads to physical and psychological outcomes for health-care workers, so this study aims to investigate the mental health outcomes (including general health, generalized anxiety disorder and posttraumatic stress disorder) in health-care workers in Rafsanjan, Iran.

By using convenience sampling, this cross-sectional study was conducted on 332 health-care workers working in public hospitals in southern Iran. Data collection lasted from March to April 2020. General Health Questionnaire (GHQ-28), Generalized Anxiety Disorder 7-item (GAD-7) and Impact of Event Scale were used to collect data. The data were then analyzed by using SPSS 25 and descriptive and inferential statistics (chi-square and multivariate logistic regression).

In total 45.5% of the participants had psychological disorder according to GHQ. In addition, 25.3% of the participants had GAD and 31.6% had posttraumatic stress disorder (PTSD). The results using multivariate logistic regression showed that only income was significantly associated with psychological disorders (95% confidence interval for odds ratio: 1.32–6.45, P = 0.008).

According to the results, the incidence of GAD and PTSD was high among health-care workers. Therefore, it is recommended that the psychological skills of health-care workers be strengthened through counseling and training programs.

This paper provides a novel analysis of mental health in health-care workers in Iran.

On a global scale, the Muslim-friendly hospitality business has intensified hotel competition. Given the paucity of research on the important service quality characteristics of Muslim-friendly hotels, this study aims to identify the major themes encountered by tourists at Muslim-friendly hotels.

The research used content analyzes (qualitative) to examine 1,250 reviews using Leximancer software. Data were gathered from the online travel website booking.com. The top 10 Islamic hotels according to Crescent ranking were taken into a data set.

Qualitative (narratives) analysis showcased nine key themes, namely, “hotel,” “staff,” “food,” “room,” “location,” “pool,” “facilities,” “cleanliness” and “Wi-Fi.” Furthermore, the findings of this study contribute to filling research voids in the literature by distinguishing themes linked with halal hotel “satisfaction” from those associated with “dissatisfaction.”

The findings of this research offer valuable visions into halal-hotel travelers’ overall experiences based on user-generated content and facilitate the identification of the dominant themes linked with a different value for money ratings.