In this paper, we present a new sampling-based bi-criteria hybrid harmony search metaheuristic for the resource-constrained project-scheduling problem (RCPSP) with uncertain activity durations (UAD) and uncertain cash...
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In this paper, we present a new sampling-based bi-criteria hybrid harmony search metaheuristic for the resource-constrained project-scheduling problem (RCPSP) with uncertain activity durations (UAD) and uncertain cash flows (UCF), with the total project duration (TPD) and the net present value (NPV) as objectives. The proposed problem-specific Sounds of Silence (SoS) metaheuristic is an appropriate hybridization of the robust SoS developed to minimize the project makespan with uncertain activity durations, and the crisp SoS developed for several a primary-secondary (PS) and bi-criteria (BC) project scheduling problems. In the presented hybrid approach, we applied a sampling-based approximation to cope with the uncertain cash flows. In order to illustrate the efficiency and stability of the proposed problem-specific SoS, which is a new member of the SoS family, we present detailed computational results for a larger and challenging project instance. The computational results reveal the fact that the modified and extended SoS is fast, efficient and robust algorithm, which is able to cope successfully with the project-scheduling problems when we replace the traditional crisp parameters with uncertain-but-bounded parameters.
We consider a parallel-machine scheduling problem with a learning effect and the makespan objective. The impact of the learning effect on job processing times is modelled by the general DeJong's learning curve. Fo...
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We consider a parallel-machine scheduling problem with a learning effect and the makespan objective. The impact of the learning effect on job processing times is modelled by the general DeJong's learning curve. For this NP-hard problem we propose two exact algorithms: a sequential branch-and-bound algorithm and a parallel branch-and-bound algorithm. We also present the results of experimental evaluation of these algorithms on a computational cluster. Finally, we use the exact algorithms to estimate the performance of two greedy heuristic scheduling algorithms for the problem. (c) 2010 Elsevier Ltd. All rights reserved.
The objective of this paper is a study of minimizing the maximum completion time min F-max, or cycle time of the last job of a given family of jobs using flow shop heuristicscheduling techniques. Three methods are pr...
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The objective of this paper is a study of minimizing the maximum completion time min F-max, or cycle time of the last job of a given family of jobs using flow shop heuristicscheduling techniques. Three methods are presented: minimize idle time (MIT);Campbell, Dudek and Smith (CDS);and Palmer. An example problem with ten jobs and five machines is used to compare results of these methods. A deterministic t-timed colored Petri net model has been developed for scheduling problem. An execution of the deterministic timed Petri net allows to computer performance measures by applying graph traversing algorithms starting from initial global state and going into a desirable final state(s) of the production system. The objective of the job scheduling policy is minimizing the cycle time of the last job scheduled in the pipeline of a given family of jobs. Three heuristicscheduling methods have been implemented. First, a sub-optimal sequence of jobs to be scheduled is generated. Second, a Petri net-based simulator with graphical user interface to monitor execution of the sequence of tasks on machines is dynamically designed. A deterministic t-timed colored Petri net model has been developed and implemented for flexible manufacturing systems (FMS). An execution of the deterministic timed Petri net into a reachability graph allows to computer performance measures by applying graph traversing algorithms starting from initial global state to a desirable final state(s) of the production system.
The objective of this paper is a study of minimizing the maximum completion time minF max , or cycle time of the last job of a given family of jobs using flow shop heuristicscheduling techniques. The methods are Mini...
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The objective of this paper is a study of minimizing the maximum completion time minF max , or cycle time of the last job of a given family of jobs using flow shop heuristicscheduling techniques. The methods are Minimize Idle Time (MIT)); Campbell, Dudek and Smith, (CDS); and Palmer. An example problem with ten jobs and five machines is used to compare results of these methods. A deterministic timed colored Petri net model has been developed for scheduling problem. An execution of the deterministic timed Petri net allows to compute performance measures by applying graph traversing algorithms starting from initial global state and going into a desirable final state(s) of the production system. The objective of the job scheduling policy is minimizing the cycle time of the last job scheduled in the pipeline of a given family of jobs. Three heuristic flow shop scheduling methods have been implemented. First a sub-optimal sequence of jobs to be scheduled has been generated. Secondly, a Petri net-based simulator with graphical user interface to monitor execution of the sequence on machines is dynamically designed.
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