This study investigates the relationship between social performance and corporate financial performance based on the information of companies listed in Tehran Stock Exchange -Iran. Today, economic entity has to identify the needs of their surrounding environment and community and in general interested parties to continue their survival and link with executive operation of the manufacturing of their products and by explaining the necessities of community provide the best services and achieve their organizational goals by selling more products. Overall, the process to identify community needs and interested parties and surrounding environment and provide services to them placed in social performance framework which is considered as the important issues to achieve success for organizations in today's competitive world. Therefore, we can say that the companies which do better their social functions financially might be in a desirable place than other competitor. In this study have been selected 90 companies of Tehran stock exchange based on elimination sampling and in order to investigate whether good social performance also leads to better financial performance. Financial variables are ROA and ROE and social variables contain five dimensions of Mark vinola model which obtain from tracking in financial statements and notes and based on score between -2 and +2. Finally, we conclude that there is no significant relationship between the social performance and corporate financial performance.
Inappropriate inventory control policies and its incorrect implementation can cause improper operation and uncompetitive advantage of organization logistic operation in the market. Therefore, analysis inventory control policies are important to be understood, including carrying cost, ordering cost, warehouse renting cost, and buying cost. In this research, Economic Order Quantity (EOQ) problem in fuzzy condition is reviewed in two different situations. The first model concerned to costs (carrying cost, ordering cost, warehouse renting cost and buying cost), which is considered as triangular fuzzy numbers. The second model was in addition to inventory the cost system, in which annual demand is also reviewed as fuzzy numbers. In each model, graded mean integration representation (GMIR) deffuzification was used for parameters deffuzification. Then, the final objective from this analysis was to obtain economic quantity formula through derivation.
One of the discussed topics in scheduling problems is Dynamic Flexible Job Shop with Parallel Machines (FDJSPM). Surveys show that this problem because of its concave and nonlinear nature usually has several local optimums. Some of the scheduling problems researchers think that genetic algorithms (GA) are appropriate approach to solve optimization problems of this kind. But researches show that one of the disadvantages of classical genetic algorithms is premature convergence and the probability of trap into the local optimum. Considering these facts, in present research, represented a developed genetic algorithm that its controlling parameters change during algorithm implementation and optimization process. This approach decreases the probability of premature convergence and trap into the local optimum. The several experiments were done show that the priority of proposed procedure of solving in field of the quality of obtained solution and convergence speed toward other present procedure.Keywords: Optimization, Parallel Machines, Genetic Algorithm, Dynamic and Adjustment of controlling parameters RESUMO Um dos tópicos discutidos na programação de problemas é a Flexibilização Dinâmica da Produção com Máquinas Paralelas (FDPMP). Pesquisas mostram que este problema, por conta de sua natureza côncava e não-linear, usualmente possui vários locais ideais. Alguns dos pesquisadores de programação de problemas pensam que a Genética dos Algoritmos (AG) são abordagens apropriadas para resolver os problemas de otimização desse tipo. Mas pesquisadores mostram que uma das desvantagens do Algoritmo Genético clássico é a convergência prematura e a probabilidade de armadilha dentro do local ideal. Considerando estes fatos, a presente pesquisa, representa um algoritmo genético desenvolvido em que seus parâmetros de controle mudem durante a implementação e otimização do processo. Esta abordagem reduz a probabilidade de convergência prematura e de armadilhas dentro de um local ideal. A maior parte dos experimentos realizados, mostram que a prioridade do procedimento proposto de solucionar no campo da qualidade da obtenção de solução e aceleração de convergência em direção da presença de outro procedimento.
Today, by developing technology and presenting Object-Oriented and Concurrent systems, new modeling languages with powerful mathematical and formulaic base are needed. UML as an Object-Oriented modeling language is needed a powerful mathematical and formulaic base for its symbols, besides, Petri Nets as a language for Concurrent systems need to have symbols for representing Object-Oriented models. In many complex systems, model presenting by Petri Nets caused model complexity and designer's perplexity and also due to wide changes in such systems, its part by part presenting by means of UML diagram is not possible. The aim of the paper is to present interface model called Object Oriented Petri Nets and its relevant software for converting Petri Nets complex model to various UML diagrams, in order to benefit from advantages of Petri Nets and UML model. In this model, Object Orienting main parts such as Object, Class, Encapsulation and Inheritance are presented with special symbols
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.