طراحی الگوی برنامه ریزی راهبردی مدیریت پروژه در شرایط نااطمینانی (مقاله علمی وزارت علوم)
درجه علمی: نشریه علمی (وزارت علوم)
آرشیو
چکیده
با توجه به نقش کلیدی ظرفیت مخازن در افزایش و پایداری تولید نفت خام و جلوگیری از نوسانات روزمره ناشی از مشکلات عملیاتی تولید و همچنین حفظ ظرفیت ذخیره سازی در صادرات نفت، حداقل سازی کلیه هزینه ها و در سرویس قرار گرفتن این مخازن، راهبرد اساسی وزارت نفت می باشد. مسئله زمان بندی پروژه با منابع محدود، از مهم ترین دسته مسائل در زمینه ی موضوعات مدیریت راهبردی در پروژه ها می باشد که در سال های اخیر به شدت مورد توجه محققین قرار گرفته است. در این تحقیق، مدل برنامه ریزی استوار برای مسئله یکپارچه سفارش دهی مواد و زمان بندی پروژه در شرایط وجود عدم قطعیت، وقفه های تقویمی، تجدیدناپذیری، فسادپذیری و سناریوهای مختلف اجرای پروژه بر نمونه واقعی تعمیر مخزن سقف شناور نفت خام ارائه می شود. مدنظر قرار دادن همزمان عوامل در قالب این مدل منجر به نزدیک تر شدن مدل به شرایط دنیای واقعی، کاربردی تر شدن نتایج و بهبود کیفیت نتایج خواهد شد. مدل تابع هدف حداقل سازی کلیه هزینه ها شامل هزینه های سفارش دهی، نگهداری، خرید و جریمه تأخیر منهای پاداش بابت زودتر تحویل دادن پروژه بود و با رویکرد امکانی نسبت به استوارسازی مدل اقدام شد. پس از ارائه مدل، یک روش حلّ ترکیبی از الگوریتم ژنتیک و نرم افزار GAMS برای حل مسائل عددی در اندازه های مختلف طراحی شد. همچنین، موردپژوهی های پروژه تعمیرات مخزن سقف شناور نفت به صورت عددی طراحی و با رویکرد موردنظر حل شد. نتایج حکایت از کاهش قابل ملاحظه زمان حل با استفاده از رویکرد ترکیبی این تحقیق داشت.Designing a strategic planning model for project management in uncertainty situations
IntroductionBy passing time and the increase in the volume of projects, as well as the diversification of the tools used to complete a project, the need to change project planning methods from traditional to novel one is well felt. In big projects or in the term mega projects such as construction of refinery, airport, spaceship, satellite, subway construction and the like, it is necessary to create a suitable plan and schedule in such a way that limited and valuable resources are fully utilized to achieve the goals of the project according to three sides. The triangle of the project means time, cost and quality to be realized. In classical approaches such as the critical chain, it is assumed that project resources are available indefinitely. After that, the assumption of the limitation of these resources was added to the model, and such issues are in the category of project planning with limited resources. Considering the key role of storage tank capacity in increasing and sustainability of oil production and preventing daily fluctuations due to production-related operational problems as well as maintaining storage capacity in oil exports, minimizing all costs and being included in the service of tanks is the main strategy at the Ministry of Petroleum. The resource-constrained project scheduling problem is one of the most important techniques in the field of project management that has attracted a lot of researchers in recent years. Methodology Classical approaches such as the critical chain assume that project resources are unlimited. However, this assumption does not make sense in most projects. Subsequently, the resource constraint assumption was added to the model. Such problems are called resource-constrained project scheduling problems. Most studies assume that activities are performed in an ideal setting and that the proposed schedule can be executed exactly according to plan. The existence of uncontrollable factors such as lack of access to resources, the addition of unforeseen activities to the project, and bad weather conditions practically lead to the failure to achieve the project objectives in the desired time. This can bring significant costs to the project. Therefore, one of the main challenges facing construction projects is the existence of uncontrollable factors. The effect of these factors on the project can be greatly reduced if different scenarios are predicted in the planning done for the project and the planning is done based on these scenarios. A robust optimization is a new approach that has been proposed in recent years to deal with data uncertainty in various scenarios. In this approach, near-optimal solutions are considered that are highly feasible and resistant to change. In other words, the feasibility of the solution obtained in different scenarios is guaranteed by slightly deviating from the value of the objective function. Results and Discussion Accordingly, in this study, a robust optimization approach is used to deal with changes in different scenarios to minimize the effect of different modes of events in the project on the accuracy of the plans made. In real conditions, ignoring some limitations and realities in modeling can reduce the applicability of the proposed model. Therefore, in this study, several important issues in modeling are considered. These issues include non-renewability, perishability, discounts on project resources, uncertainty, and lag times. The following is a brief description of these concepts for more familiarity with them. In this study, a robust planning model for the problem of robust integrated project scheduling and material ordering under uncertainty, lag times, non-renewability, perishability, and various project implementation scenarios was provided. Simultaneous consideration of the above in the model brought the model closer to real-world conditions, made the results more practical, and improved the quality of results. The model had the objective function to minimize the total cost, including ordering, maintenance, purchasing, and penalties for delay minus the bonus for hastening the project delivery. Conclusion Model robustification perform with a possibilistic approach. After providing the model, numerical problems of different sizes were solved using a hybrid solution method of genetic algorithm and GAMS software. Moreover, a sample problem concerning an oil resource repair project and several numerical problems were designed and solved using the desired approach. Also, the case studies of the oil floating roof tank repair project were numerically designed and solved with the desired approach. The results indicated a significant reduction in the solution time using the combined approach of this research.
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