Scheduling
Saeideh Naderi; Mohsen Vaez-Ghasemi; farzad movahedi sobhani
Abstract
The Resource-Constrained Project Scheduling Problem (RCPSP) is a general one in scheduling which possesses various applications in production, production scheduling, project managing and other criteria. This issue has been studied since 1960 and is very complicated. In this study, the common presuppositions ...
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The Resource-Constrained Project Scheduling Problem (RCPSP) is a general one in scheduling which possesses various applications in production, production scheduling, project managing and other criteria. This issue has been studied since 1960 and is very complicated. In this study, the common presuppositions and limitations regarding such problems will be investigated in addition to their reliability in modelization in order to investigate the possibility of availability of renewable resources using a new attitude. The objective of modelization of RCPSP is quantification of total costs and minimization of delays in projects. Therefore, in order to mathematically modelize RCPSP, non-linear complex integer math programming which transforms into a linear programming model using the features of exponential functions is used. In order to solve the final linear math problem, some experimental examples will be designed in different dimensions, so that the performance and efficiency of the designed model are studied. For solving problems with low dimensions , the Epsilon Constraint multi-objective optimization method is used in an exact optimization software like Lingo. In order to find out the solutions of the ones whose dimensions are high, which exact methods can not solve,the meta-heuristic algorithm called NSGA-II which is a strong one to optimize multi objective problems is used. The results of using these algorithms and the statistical analysis which shows their reliability as 95 percent , indicates that the performance is suitable for genetic algorithms. Therefore this meta-heuristic algorithm has more efficiency and more apposite performance for the recommended model compared with the software of exact optimization. Using the designed math model ,this study can result in decreasing the times of delay in projects and the costs in the scheduling problem and also increasing the reliability when activities are multi-mode.
Engineering Optimization
Parviz Tohidi Nasab; Mohsen Vaez Ghasemi; Ghasem Tohidi
Abstract
The Aircraft Scheduling Problem (ASP) refers to allocating each aircraft to the optimal take-off and landing time and the appropriate runway. This problem is the allocation of aircraft to the desired runway so that the total damage due to delays or haste in landing or take-off of all aircraft is minimized. ...
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The Aircraft Scheduling Problem (ASP) refers to allocating each aircraft to the optimal take-off and landing time and the appropriate runway. This problem is the allocation of aircraft to the desired runway so that the total damage due to delays or haste in landing or take-off of all aircraft is minimized. Runway allocation, landing and take-off sequences, and scheduling for each aircraft must be done in a predetermined time window. Time should also be considered as the time of separation between landings and take-offs due to the wake vortex phenomenon. In general, the purpose of such problems is to make maximum use of the runway. Therefore, in this study, a mathematical model of robust landing and take-off scheduling at an airport is provided, assuming no access to the airport runway at certain times. Moreover, delays and haste in landing and take-off on the runway, limited access to aircraft, runway repair time, and the possibility of runway disturbances are investigated. Robust optimization is used to deal with uncertainty at take-off and landing times. Finally, Genetic and Imperialistic Competitive Algorithm are used to evaluate and analyze the problem because it is NP-HARD problem. The results indicate the ability of the proposed algorithms to find high-quality solutions in a short computation time for problems up to 7 runways and 60 aircraft.
