Equity distribution of quality evaluation reports to doctors in health care organizations

Melhim LK, Jemmali M, El Ayeb F, Alharbi H, Banjar A. Novel variable neighborhood search heuristics for truck management in distribution warehouses problem

Logistics and sourcing management are core in any supply chain operation and are among the critical challenges facing any economy. The specialists classify transport operations and warehouse management as two of the biggest and costliest challenges in logistics and supply chain operations. Therefore, an effective warehouse management system is a legend to the success of timely delivery of products and the reduction of operational costs. The proposed scheme aims to discuss truck unloading operations problems. It focuses on cases where the number of warehouses is limited, and the number of trucks and the truck unloading time need to be manageable or unknown. The contribution of this article is to present a solution that: (i) enhances the efficiency of the supply chain process by reducing the overall time for the truck unloading problem; (ii) presents an intelligent metaheuristic warehouse management solution that uses dispatching rules, randomization, permutation, and iteration methods; (iii) proposes four heuristics to deal with the proposed problem; and (iv) measures the performance of the proposed solution using two uniform distribution classes with 480 trucks' unloading times instances. Our result shows that the best algorithm is O I S ~ , as it has a percentage of 78.7% of the used cases, an average gap of 0.001, and an average running time of 0.0053 s.

Novel randomization and iterative based algorithms for the transactions assignment in blockchain problem

This study focuses on the load balancing of the transactions in the blockchain. The problem is how to assign these transactions to the blocks. The objective is to guarantee a load balancing of the workload in the time of blocks. The proposed problem is an NP-hard one. To face the hardness of the studied problem, the challenge is to develop algorithms that solve the problem approximately. Finding an approximate solution is a real challenge. In this paper, nine algorithms are proposed. These algorithms are based on the dispatching-rules method, randomization approach, clustering algorithms, and iterative method. The proposed algorithms return approximate solutions in a remarkable time. In addition, in this paper, a novel architecture composed of blocks is proposed. This architecture adds the component "Balancer". This component is responsible to call the best-proposed algorithm and solve the scheduling problem in a polynomial time. In addition, the proposed work helps users to solve the problem of big data concurrency. These algorithms are coded and compared. The performance of these algorithms is tested over three classes of instances. These classes are generated based on uniform distribution. The total number of instances tested is 1350. The average gap, execution time, and the percentage of the best-reached value are used as metrics to measure the performance of the proposed algorithms. Experimental results show the performance of these algorithms and a comparison between them is discussed. The experimental results show that the best algorithm is best-mi-transactions iterative multi-choice with 93.9% in an average running time of 0.003 s.

Algorithms for the executable programs planning on supercomputers

This research dealt with the problem of scheduling applied to the supercomputer’s execution. The goal is to develop an appreciated algorithm that schedules a group of several programs characterized by their time consuming very high on different supercomputers searching for an efficient assignment of the total running time. This efficient assignment grantees the fair load distribution of the execution on the supercomputers. The essential goal of this research is to propose several algorithms that can ensure the load balancing of the execution of all programs. In this research, all supercomputers are assumed to have the same hardware characteristics. The main objective is to minimize the gap between the total running time of the supercomputers. This minimization of the gap encompasses the development of novel solutions giving planning of the executable programs. Different algorithms are presented to minimize the gap in running time. The experimental study proves that the developed algorithms are efficient in terms of performance evaluation and running time. A comparison between the presented algorithms is discussed through different classes of instances where in total the number of instances reached 630. The experiments show that the efficient algorithm is the best-programs choice algorithm. Indeed, this algorithm reached the percentage of 72.86%, an average running time of 0.0121, and a gap value of 0.0545.

Occupational Stress and Personality in Medical Doctors from Romania

Occupational stress amongst doctors has been intensively studied as doctors are exposed to several stress factors daily. The purpose of this study was to investigate if there are associations between personality dimensions and the factors that generate stress at work. We conducted a cross-sectional study of 280 medical doctors from Romania between February 2021 and September 2021 who were evaluated using the DECAS and ASSET Scales. Our results showed that the agreeableness and emotional stability dimensions of personality, according to the Big Five model, were statistically associated with work relationships (A p < 0.0001; ES p = 0.0005), work-life balance (A p = 0.008; ES p = 0.01), overload (A p = 0.01; ES p = 0.001), job security (A p < 0.0001; ES p = 0.002), job control (A p = 0.001; ES p = 0.009), resources and communication (A p = 0.0002; ES p < 0.0001), and job conditions (A p = 0.005; ES p = 0.03). The conscientiousness dimension was statistically associated with job control (p = 0.02). Doctors from different specialties experienced stress differently, with psychiatrists and doctors from preclinical specialties reporting the lowest levels of stress. Internists and surgeons reported higher levels of stress. This study showed that the dimensions of agreeableness and emotional stability were both associated with variables indicative of the level of stress felt at work.

Smart-parking management algorithms in smart city

Recently, various advanced technologies have been employed to build smart cities. Smart cities aim at improving the quality of life through the delivery of better services. One of the current services that are essential for any smart city, is the availability of enough parking spaces to ensure smooth and easy traffic flow. This research proposes a new framework for solving the problem of parking lot allocation, which emphasizes the equitable allocation of people based on the overall count of people in each parking space. The allocation process is performed while considering the available parking lots in each parking space. To accomplish the desired goal, this research will develop a set of seven algorithms to reduce the gap in the number of people between parking spaces. Many experiments carried out on 2430 different cases to cover several aspects such as the execution time and the gap calculations, were used to explore the performance of the developed algorithm. Analyzing the obtained results indicates a good performance behavior of the developed algorithms. Also, it shows that the developed algorithms can solve the studied problem in terms of gap and time calculations. The MR algorithm gained excellent performance results compared to one of the best algorithms in the literature. The MR algorithm has a percentage of 96.1 %, an average gap of 0.02, and a good execution time of 0.007 s.