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| MINE3005 | Operations Research | 2+0+0 | ECTS:4 | | Year / Semester | Fall Semester | | Level of Course | First Cycle | | Status | Elective | | Department | DEPARTMENT of MINING ENGINEERING | | Prerequisites and co-requisites | None | | Mode of Delivery | | | Contact Hours | 14 weeks - 2 hours of lectures per week | | Lecturer | Doç. Dr. Uzay KARAHALİL | | Co-Lecturer | | | Language of instruction | | | Professional practise ( internship ) | None | | | | The aim of the course: | | The aim of this course is to teach students the use of scientific/mathematical decision making techniques in the field of Mining Engineering by considering system, interdisciplinary and scientific approaches. To gain the ability to build and solve models and analyze the results in order to make optimum use of limited mineral resources with the help of linear programming and goal programming techniques. |
| Learning Outcomes | CTPO | TOA | | Upon successful completion of the course, the students will be able to : | | | | LO - 1 : | Have knowledge about the history of operations research, definition, different techniques and software used in model solving | 2,3 | 1,3, | | LO - 2 : | Explains the importance of operations research techniques in the mining sector and defines their usage areas | 2,3 | 1,3, | | LO - 3 : | Build models for real mining problems using linear programming and goal programming techniques | 2,3 | 1,3, | | LO - 4 : | Solves a built model with graphical method, simplex method and computer softwares, presents the outputs to the manager by associating them with the problem structure | 2,3 | 1,3, | | LO - 5 : | Analyses and interprets the model outputs and determines the effects of each constraint or coefficient change on the objective and outputs | 2,3 | 1,3, | | LO - 6 : | Provides alternative solutions by evaluating the possible risks and opportunities of the organization that owns the problem | 2,3 | 1,3, | | CTPO : Contribution to programme outcomes, TOA :Type of assessment (1: written exam, 2: Oral exam, 3: Homework assignment, 4: Laboratory exercise/exam, 5: Seminar / presentation, 6: Term paper), LO : Learning Outcome | | |
| Basic principles of operations research, introduction of basic concepts such as system, model, objective-constraints, history and relation with mining sciences, basic elements of operations research. Model building and solving, testing and implementation of solutions, modelling methods, linear and goal programming, application of these methods to mining problems. Structure and components of linear programming (LP), construction of models of sample problems by LP, construction of models of mining problems by LP, solutions by graphical and simplex methods. Sensitivity analysis (economic analysis), duality concept in DP model solutions, sensitivities of resource values, objective function coefficients and adding a new product. Introduction and applications of LINDO software. Introduction to goal programming, construction of goal programming models, determination of objectives and their priorities, solutions by modified simplex method. Solution of sample problems with goal programming. |
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| Course Syllabus | | Week | Subject | Related Notes / Files | | Week 1 | Introduction to operations research (definition and history), applications in mining engineering | | | Week 2 | Basic principles of operations research, introduction of basic concepts such as system, model, objective-constraints | | | Week 3 | Introduciton to linear programming (LP) | | | Week 4 | Modelling of sample problems with LP | | | Week 5 | Modelling of mining problems with LP | | | Week 6 | Solution of LP models: Graphical method | | | Week 7 | Solution of LP models: Simplex method | | | Week 8 | Sensitivity analysis (Economic analysis) | | | Week 9 | Mid-term exam | | | Week 10 | Sensitivity analysis (Economic analysis, continued) | | | Week 11 | Introduction and applications of LINDO software | | | Week 12 | Integer programming | | | Week 13 | Establishing models of mining problems with IP | | | Week 14 | Introduction to goal programming: Model building and solution | | | Week 15 | Solution of sample problems with Goal Programming technique | | | Week 16 | Final exam | | | |
| 1 | Winston, W.L. 2004; Operations Research: Applications and Algorithms, Fourth Edition, Thomson, ISBN 0-534-38058-1, 1418 p. | | | 2 | Hillier, F.S., Lieberman, G.J., 1990; Introduction to Operations Research, Mc Graw-Hill, NewYork,5. Baskı | | | |
| 1 | Halaç, O. 1991; Kantitatif Karar Verme Teknikleri (Yöneylem Araştırması), 3. Baskı, Evrim Dağıtım, İstanbul. | | | 2 | Anderson, D.R., Sweeney, D.J., Williams, T.A. 1997; An İntroduction to Management Science, Quantitative Approaches to Decision Making, Eighth Edition, West Publishing Com., Minneapolis. | | | |
| Method of Assessment | | Type of assessment | Week No | Date | Duration (hours) | Weight (%) | | Mid-term exam | 9 | 11/11/2022 | 1 | 30 | | Homework/Assignment/Term-paper | 12 | 02/12/2022 | 1 | 20 | | End-of-term exam | 16 | 04/01/2023 | 1 | 50 | | |
| Student Work Load and its Distribution | | Type of work | Duration (hours pw) | No of weeks / Number of activity | Hours in total per term | | Yüz yüze eğitim | 2 | 15 | 30 | | Sınıf dışı çalışma | 1 | 3 | 3 | | Arasınav için hazırlık | 5 | 4 | 20 | | Arasınav | 1 | 1 | 1 | | Uygulama | 1 | 15 | 15 | | Ödev | 4 | 5 | 20 | | Dönem sonu sınavı için hazırlık | 6 | 5 | 30 | | Dönem sonu sınavı | 1 | 1 | 1 | | Total work load | | | 120 |
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