Journal of Computational Algorithms and Numerical Dimensions
Volume:2 Issue: 2, Spring 2023

This study, conducted in Iran's pharmaceutical industry, investigates the development of cost-effectiveness capabilities, a vital component of operational capabilities. It presents five essential hypotheses contributing to these capabilities. Capable human resources, especially in crisis management related to environmental obstacles like international sanctions, foster creativity and cost-effectiveness. Hardware and software infrastructure supports international collaborations, enhancing overall quality. Documentation, organizational knowledge, and capacity enhancement further contribute to cost-effectiveness capabilities. Effective operations management, standardized routines, and the emergence of new routines stimulate creativity and cost reduction. This research offers insights into the formation of cost-effectiveness capabilities and underscores the significance of internal resources, collaborations, and efficient management practices. While focused on Iran's pharmaceutical sector, the proposed model can serve as a valuable framework for studying influencing factors on cost-effectiveness capabilities in other industries and countries.

In the current research, the dataset for conducting data mining calculations was generated based on a sample with 2,000 data, reports of the general manager of the textile industry of Iran's Ministry of Industry, Mine and Trade (information from 240 industrial units and 630 spinning and weaving units were collected), and textile industry plants in Borujerd as the place for implementing the plan between 2015 and 2019, a period 6 month each year. Due to extensive information from the textile industry (with the help of the Ministry of Industry, Mine and Trade), the current research is unique. Using IBM SPSS Modeler 18, the most significant results of datamining calculations to extract knowledge are as follows, which are arranged based on main predictors of the research: predicting models of "strategy innovation in net with data code (A5)" with the prediction wight of 0.34; "technology innovation in net with data code (A1)" with the prediction wight of 0.30; "work environment innovation in net with data code (A3)" with the prediction wight of 0.16; Quality innovation in net with data code (A4)" with the prediction wight of 0.15; "employe  innovation in net with data code (A2)" with the prediction wight of 0.10 are utilized to accurately analyze preventive maintenance in interaction with production.

This paper deals with the single machine scheduling problem with sequence-dependent setup time and learning effect on processing time, where the objective is to minimize total earliness and tardiness of the jobs. A Mixed Integer Linear Programming (MILP) model capable of solving small-sized problems is proposed to formulate this problem. In view of the NP-hard nature of the problem, the Hybrid Particle Swarm Optimization (HPSO) algorithm is proposed to solve the large-sized problems. In order to utilize Particle Swarm Optimization (PSO) to solve the scheduling problems, the proposed HPSO approach uses a random key representation to encode solutions, which can convert the job sequences to continuous position values. Also, the local search procedure is included within the HPSO to enhance the exploitation of the algorithm. The performance of the proposed HPSO is verified for small and medium-sized problems by comparing its results with the best solution obtained by the LINGO. In order to test the applicability of the proposed algorithm to solve large-sized problems, 120 instances are generated, and the results are compared with a Random Key Genetic Algorithm (RKGA). The results show the effectiveness of the proposed model and algorithm.

Improving buildings' behaviour by reducing lateral loads' effect is a new topic in earthquake engineering. It is based on reducing the energy applied to the structure through its depreciation. Structures can consume much energy in an earthquake due to their ductility. The use of energy-consuming systems in buildings allows structural members to remain resilient. Therefore, this research investigates a combined neural network-based method for optimizing Added Damper and Stiffness (ADAS) dampers in steel buildings. Thus, the seismic behaviour of each is addressed by modelling a 15-story steel structure with steel bracing in at least four reinforcement modes with ADAS damper. The selection criterion of these structures is the study of high-rise structures, and the study of finding the optimal state of reinforcement with dampers is discussed. Incremental Dynamic Analysis (IDA) using at least ten accelerograms is used in this regard. In this regard, Etabs software is used for the initial design of structures, nonlinear analysis, and optimization of OpenSees and Matlab software. It was observed that in different types of dampers arrangement, different behaviour is observed in structures. Also, the type of mirrors if due to the different hardness and performance of each damper, also led to a change in the behaviour of the structures modelled in this study. Of course, what was observed so that it is not possible to say with certainty which mode leads to better performance in structures because the performance of all four types of attenuators is very close to each other. Still, it can be said that all dampers can be considered suitable improvement options according to the employer's conditions in terms of executive capability. Dampers increase the relative displacement of the floors by improving the structure's stiffness, thereby reducing structural and non-structural damage. Triangular Added Damper and Stiffness (TADAS) and ADAS dampers have good seismic behaviour, can withstand a large number of cycles, and can absorb a large amount of earthquake energy without loss of stiffness and resistance. The use of dampers in determining the overall and local response of the sample structures under the earthquake record will positively affect the reinforcement of the structures.

The new generation of wireless networks (LTE advance and WIMAX) supports many services that consume many resources (such as VOIP, video conference …). Adding multi-media services to wireless communication systems provide new challenges of resource allocation. This paper proposes a resource scheduling downlink algorithm for LTE networks. In the proposed algorithm for different types of services, priorities are defined to guarantee transitions of GBR services that need high QoS. This method also considers channel quality and buffer status to achieve higher throughput for non-GBR services. The proposed algorithm is simulated and compared with the proportional fair algorithm. Simulation results show that the suggested algorithm can increase system throughput and QoS of real-time services at the cost of a certain amount of throughput and QoS of non-real times.

Until the 1980s, the system for assessing the performance of organizations with specific structures has been based on economic and financial indexes. The previous methods that were frequently used for performance assessment were mainly focused on the economic-financial aspects of the organization. However, at present, due to vast human needs, sensitive cognitive, fundamental parameters in social organizations that are based on realities, are very effective, and meet scientific criteria have come into vogue. These parameters rely on experience, observation, experiment, hypothesis, and theory. Balanced Scorecard (BSC) seeks to make a balance between financial and economic objectives as outcomes of past performance (past-oriented indexes) and three indexes of customer processes, learning and growth, and development of human and social forces (future-oriented).Data Envelopment Analysis (DEA) is a non-parametric method for measuring the outputs or efficiency of homogeneous units with different inputs and outputs. However, in cases where there are numerous inputs and outputs with some similarities, their efficiency can be measured by two-level DEA, i.e., classifying them and using common weights.In primitive social institutions, the inputs of social systems are mainly limited and clear. However, in modern, complex, standardized systems, the input is both expanded and diversified. Therefore, in this paper, we have tried to use BSC as an instrument for designing performance assessment indexes and two-level DEA as an instrument for measurement.