Article for an International Academic Journal
Computers and Industrial Engineering (CAIE) is one of the important international journal, publishes original contributions to the development of new computerized methodologies for solving industrial engineering problems and their application. In 2016, CAIE had an Impact Factor of 2.623 and a 5-year Impact Factor of 2.859. It earned a CiteScore of 3.41, placing it in the 96th percentile among industrial engineering journals.
It publishes original contributions on the development of new computerized methodologies for solving industrial engineering problems, as well as the applications of those methodologies to problems of interest in the broad industrial engineering and associated communities. The journal encourages submissions that expand the frontiers of the fundamental theories and concepts underlying industrial engineering techniques.
CAIE also serves as a venue for articles evaluating the state-of-the-art of computer applications in various industrial engineering and related topics, and research in the utilization of computers in industrial engineering education. Papers reporting on applications of industrial engineering techniques to real life problems are welcome, as long as they satisfy the criteria of originality in the choice of the problem and the tools utilized to solve it, generality of the approach for applicability to other problems, and significance of the results produced.
A major aim of the journal is to foster international exchange of ideas and experiences among scholars and practitioners with shared interests all over the world. In that scope, the article of Rasmi, Kazan and Turkay has published in CAIE journal. The article has been prepared based on the thesis article of Cem Kazan (An Optimization Model for the Incorporation of the Cultural Environment in the Aggregate Production Problem), and the exact solution method for multi-objective mixed-integer linear programs (MOMILP) method of Seyyed Amir Babak Rasmi.
In their paper, they present a multi-objective aggregate production planning (APP) model to analyze economic, social, environmental, and cultural pillars inclusively; moreover, each pillar includes several sub-pillars in the model. The resulting model includes an accurate representation of the problem with binary and continuous variables under sustainability considerations. They illustrate the effectiveness of the model in an appliance manufacturer and solve the problem using an MOMILP. They find a large number of the non-dominated (ND) points in the objective function space and analyze their trade-offs systematically. They show how this framework supports multiple criteria decision making process in the APP problems in the presence of sustainability considerations. Their approach provides a comprehensive analysis of the ND points of sustainable APP (SAPP) problems, and hence, the trade-offs of objective functions are insightful to the decision makers.