Performance analyses of weighted superposition attraction-repulsion algorithms in solving difficult optimization problems.

The purpose of this paper is to test the performance of the recently proposed weighted superposition attraction-repulsion algorithms (WSA and WSAR) on unconstrained continuous optimization test problems and constrained optimization problems. WSAR is a successor of weighted superposition attraction algorithm (WSA). WSAR is established upon the superposition principle from physics and mimics attractive and repulsive movements of solution agents (vectors). Differently from the WSA, WSAR also considers repulsive movements with updated solution move equations. WSAR requires very few algorithm-specific parameters to be set and has good convergence and searching capability. Through extensive computational tests on many benchmark problems including CEC'2015 and CEC'2020 performance of the WSAR is compared against WSA and other metaheuristic algorithms. It is statistically shown that the WSAR algorithm is able to produce good and competitive results in comparison to its predecessor WSA and other metaheuristic algorithms.

A classification scheme for agent based approaches to dynamic optimization.

Several papers in the literature employ agent-based modeling approach for providing reasonable solutions to dynamic optimization problems (DOPs). However, these studies employ a variety of agent-based modeling approaches with different strategies and features for different DOPs. On the other hand, there is an absence in the literature of a formal representation of the existing agent-based solution strategies. This paper proposes a representation scheme indicating how the solution strategies with agent-based approach can be summarized in a concise manner. We present these in a tabular form called "Agent Based Dynamic Optimization Problem Solution Strategy" (ABDOPSS). ABDOPSS distinguishes different classes of agent based algorithms (via communication type, cooperation type, dynamism domain and etc.) by specifying the fundamental ingredients of each of these approaches with respect to problem domain (problems with dynamic objective functions, constraints and etc.). This paper also analyzes 18 generic studies in the literature employing agent-based modeling based on ABDOPSS.

Application of cost/benefit analysis for surgical gown and drape selection: a case study.

BACKGROUND: The selection of medical textiles is an important subject for the health care sector in terms of benefits and costs. The basic cost calculation does not always yield to proper results in product selection; it would even mislead. It is usually a complicated task to give a decision whether to use reusable or single-use products, especially when the patient and surgeons lives are in consideration. The objective of the present paper is to carry out a cost/benefit study to help hospital managers and surgical team in comparing reusable and single-use surgical gowns and drapes. METHODS: A detailed case study was carried out to determine the net benefits and costs associated with reusable and single-use surgical gown and drape use in the University of Gaziantep Hospital. The Analytic hierarchy process (AHP) is used to evaluate qualitative benefit data. The relevant data were determined through the literature research and interviews with the doctors, administrators, and personnel of related departments (such as infection control, cleaning, and others) in the hospital. The benefit/cost ratios of the alternatives have been examined, and a sensitivity analysis has been carried out to measure the impact of changes in costs and benefits. CONCLUSION: After the study, it is concluded that, even though cost is relatively higher, single-use gown and drape sets provide the highest benefit rates. Reduction of prices of single-use sets will make them more competitive and attractive in the health care sector.