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Scheduling, or planning, is widely recognized as a very important step in several do- mains such as high level synthesis, real-time systems, and every-day applications. Given a problem described by a number of actions and their relationships, finding a schedule, or a plan, means to find a way to perform all the actions minimizing a specific cost fu...
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Context 1
... The type of resources that are possible to adopt for each operation, e.g., we can suppose to use a particular tool (or employee), namely op, able to complete more than one kind of operation. Figure 2 shows some of the possible scheduling instances, with different set of resources (op1, op2, op3) available: ...
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... In Figure 2(a) there is no resource limit. All operations needing op1 can run in the first time step as there are enough resources to execute them in parallel. ...
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... In Figure 2(b) two resources are available for operator op1. As a consequence the third task needing the operator op1 has to be delayed until the second time unit. ...
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... In Figure 2(c) one single resource is available for each operation. Then, just a single op1 operator can be used in each single time unit. ...
Citations
... In their aircraft inspection planning model [4] Baohui takes into account factors such as the human factor, type of inspection, type of aircraft, operation location and MRO. Bruno and co-authors compare the use of different aircraft maintenance planning techniques [6]. They share their focus on aircraft inspection planning, i.e., when a plane should be stopped and what checks should be performed during the forthcoming inspection. ...
Aircraft maintenance and repair organizations (MROs) have to be competitive and attractive for both existing and new customers. The aircraft ground time at MROs should be as short as possible and cost effective without reducing the quality of the work. Process optimization in MROs requires the continuous improvement of processes and the elimination of non-value-added activities during maintenance checks. There is, on the one hand, an obligation to follow the prescribed procedures and, on the other hand, pressure for time and cost reduction. The aircraft servicing process has been analysed according to a lean methodology. The optimization of logistics processes is recognized as the most promising method for reducing the maintenance service time and costs of spare parts. The probability of aircraft faults is calculated on the basis of historic data from previously completed service projects. Aircraft parameters, such as aircraft type, operator, aircraft age, flight hours, flight cycles, engine type and operation location, are taken into consideration in the fault forecasting. The fault probability is used as an indicator for defining a priority list for the accomplishment of jobs included in the aircraft maintenance service. The proposed methodology was validated and confirmed on four different projects. © 2017, Polish Academy of Sciences Branch Lublin. All rights reserved.
... cently attained interesting results in the framework of hardware scheduling [4]- [9], as an alternative to integer linear programming [10] and heuristic techniques [11], [12]. The key idea of the symbolic approach is to use a set of nondeterministic finite automata to describe the behavior of each operation in the system. ...
... In [6], [8], [14], and [9] Cabodi et al. adapted the previous model to support conventional model checking procedures for control-dependent systems. More specifically, alternative sub-traces were transformed into concurrent behaviors, subsequently followed in parallel. ...
... The resulting automaton, further restricted by several constraints, incorporates all the allowed system behaviors, and can indeed be used for solving the scheduling problem. Following [8] and [9], the overall formulation is ...
The task graph cost-optimal scheduling problem consists in scheduling a certain number of interdependent tasks onto a set of heterogeneous processors (characterized by idle and running rates per time unit), minimizing the cost of the entire process. This paper provides a novel formulation for this scheduling puzzle, in which an optimal solution is computed through a sequence of binate covering problems, hinged within a bounded model checking paradigm. In this approach, each covering instance, providing a min-cost trace for a given schedule depth, can be solved with several strategies, resorting to minimum-cost satisfiability solvers or pseudo-Boolean optimization tools. Unfortunately, all direct resolution methods show very low efficiency and scalability. As a consequence, we introduce a specialized method to solve the same sequence of problems, based on a traditional all-solution SAT solver. This approach follows the “circuit cofactoring” strategy, as it exploits a powerful technique to capture a large set of solutions for any new SAT counter-example. The overall method is completed with a branch-and-bound heuristic which evaluates lower and upper bounds of the schedule length, to reduce the state space that has to be visited. Our results show that the proposed strategy significantly improves the blind binate covering schema, and it outperforms general purpose state-of-the-art tools.
