In this paper we propose a robust genetic algorithm for the multi-mode resourceconstrained project scheduling problem. We present a new representation for the solutions to this problem, which includes an additional bit indicating the scheduling scheme used to construct the schedule, forward or backward. Moreover, we have developed new genetic operators which operate over this representation, ex...

This paper introduces a novel approach for solving the multimode resource-constrained project scheduling problem (MRCPSP), in which multiple execution modes are available for each of the activities of the project. The new approach applies simple agent learning devices, i.e. learning automata, to construct the project schedules. We present some comparative results, to show that our decentralized...

In this work we present a multi-neighborhood, parallel local search approach for the Multi-Mode Resource-Constrained Multi-Project Scheduling Problem (MMRCMPSP). The search in multiple neighborhoods is conducted in parallel with dynamic load balancing among processors. Our solver works with an indirect solution representation and navigates through space of the feasible solutions by combining he...

NP-completeness and other complexity proofs often merely state that the problem at hand is a generalization of some other intractable problem. This proof technique relies on the widely accepted assumption that complexity results hold regardless of the model formulation used to represent the problem and the encoding used to represent its instances. However, recent results indicate that these ass...

Complexity proofs often restrict themselves to stating that the problem at hand is a generalization of some other intractable problem. This proof technique relies on the widely accepted assumptions that complexity results hold regardless of the model formulation used to represent the problem and the encoding used to represent its instances. However, recent results indicate that these assumption...

In this work we present a multi-neighborhood, parallel local search approach for the Multi-Mode Resource-Constrained Multi-Project Scheduling Problem (MMRCMPSP). The search in multiple neighborhoods is conducted in parallel with dynamic load balancing among processors. Our solver works with an indirect solution representation and navigates through space of the feasible solutions by combining he...

In this paper a novel technique for resource-constrained loop pipelining is presented. RCLP is based on several dependence graph operations: loop unrolling, operation retiming, resource-constrained scheduling, and span reduction. All these operations are focused to nd a minimum length schedule able to be executed with a limited number of resources and thus maximizing resource utilization. Exper...

In this paper, it is supposed that a project can be shown as a metagraph. The duration of activities are discrete random variables with known probability function, also one kind of consumable and constrained resource is required to execute each activity of the project.The objective of this paper is to maximize the probability of completion of stochastic metagraph before the due date of the proj...