This paper deals with the multi mode multiple resource constrained project scheduling problem (MRCPSP),which is abstracted from modeling the formation process of virtual enterprises of agile manufacturing in the next century.
The results of mathematical examples indicate that the mathematical model and the optimization method proposed in this paper can solve the multi\|resource constrained multi\|project scheduling problem effectively.
As a branch of embedded systems, real-time embedded industrial monitor and control system has not only resource constraints that are common to embedded systems, but also specific requirements on high reliability and real-time performance.
In this paper we formulate a bi-criteria search strategy of a heuristic learning algorithm for solving multiple resource-constrained project scheduling problems.
The fact that streaming information is often generated or received onboard resource-constrained computational devices such as sensor nodes and mobile devices motivates the need for resource-awareness in data stream processing systems.
To achieve trust, authentication, the resource-constrained trust negotiation is addressed, and traditional authentication key exchange protocol is extended.
The best lower bound for the Resource Constrained Project Scheduling Problem is currently based on the resolution of several large Linear Programs (Brucker >amp;amp; Knust, EJOR, 107: 272-288, 1998).
Our motivation to study these problems is their relevance in the solution of resource constrained scheduling problems, where an independence system arises as the subsets of jobs that may be scheduled simultaneously.
A network model was developed for dynamic multicast traffic grooming with resource constraints and an algorithm that can provide quality of service (QoS) was proposed.
In this letter, a scheduling scheme based on Dynamic Frequency Clocking (DFC) and multiple voltages is proposed for low power designs under the timing and the resource constraints.
We improve the job specific decomposition Lagrangian relaxation algorithm applied to industry size job shop scheduling problems with more than 10000 resource constraints.
Computational experiments with the heuristic demonstrates that it provides satisfactory results regarding the feasibility of the schedules with respect to the project due date and the nonrenewable resource constraints.
This empirical support for the use of institutional database variables is valuable in conducting institution-specific retention research under constrained resources.
The paper deals with a permutation flow-shop problem where processing times of jobs on some machines are linear, decreasing functions with respect to the amount of continuously-divisible, non-renewable, locally and totally constrained resources, e.g.
This paper proposes a methodology for sizing certain large-scale systems of reusable, capacity-constrained resources engaged in tasks of varying duration.