This paper develops a fuzzy multi-objective model for solving aggregate production planning problems that contain multiple products and multiple periods in uncertain environments. We seek to minimize total production cost and total labor cost. We adopted a new method that utilizes a Zimmermans approach to determine the tolerance and aspiration levels. The actual performance of an industrial company was used to prove the feasibility of the proposed model. The proposed model shows that the method is useful, generalizable, and can be applied to APP problems with other parameters.

This paper deals with constructing a model of fuzzy linear programming with application on fuels product of Dura- refinery , which consist of seven products that have direct effect ondaily consumption . After Building the model which consist of objective function represents the selling prices ofthe products and fuzzy productions constraints and fuzzy demand constraints addition to production requirements constraints , we used program of ( WIN QSB )  to find the optimal solution

Transportation and distribution are the most important elements in the work system for any company, which are of great importance in the success of the chain work. Al-Rabee factory is one of the largest ice cream factories in Iraq and it is considered one of the most productive and diversified factories with products where its products cover most areas of the capital Baghdad, however, it lacks a distribution system based on scientific and mathematical methods to work in the transportation and distribution processes, moreover, these processes need a set of important data that cannot in any way be separated from the reality of fuzziness industrial environment in Iraq, which led to use the fuzzy sets theory to reduce the levels of uncertainty.

International Journal on Technical and Physical Problems of Engineering

The research aims to detect the problems of educational reality faced by university professors and identify statistically significant differences in the academic problems of university instructors. It has adopted an analytical descriptive research approach to achieve research objectives and identifies the study community with professors of public and private universities. A random sample of 250 instructors was selected for the purpose of applying the questionnaire to them, knowing the academic problems encountered in the course of their work at universities, and adopting appropriate statistical means to process and analyze the data. The research concluded with a set of results, including that all fields (infrastructure, admission of

Geography of industry has been considered a branch of important economic geographical branches. This importance has been regarded as a reflection on the industrial sector contribution in economies of any state since they contribute into the total national product ; it also assimilates a huge number of labor hands . The industry of grains grinding has been considered as one of the main food industries having a main role in satisfying the need of the population from the foods. The industry is continued to use the food as daily meal . Here, it should predict the population in Baghdad and for every district until the end of 2025 and knowing either these grains grinders are able to meet and satisfy the needs of populations of flours, making s

In this study, a brand-new double transform known as the double INEM transform is introduced. Combined with the definition and essential features of the proposed double transform, new findings on partial derivatives, Heaviside function, are also presented. Additionally, we solve several symmetric applications to show how effective the provided transform is at resolving partial differential equation.

Market share is a major indication of business success. Understanding the impact of numerous economic factors on market share is critical to a company’s success. In this study, we examine the market shares of two manufacturers in a duopoly economy and present an optimal pricing approach for increasing a company’s market share. We create two numerical models based on ordinary differential equations to investigate market success. The first model takes into account quantity demand and investment in R&D, whereas the second model investigates a more realistic relationship between quantity demand and pricing.