This paper introduces a new general framework for genetic algorithms to solve a broad range of optimization problems. When designing a genetic algorithm, there may be several alternatives for a component such as crossover, mutation or decoding procedure, and it may be difficult to determine the...

Numerous exact algorithms have been developed for solving the resource-constrained project scheduling problem. Experimental studies have shown that currently even projects with only 60 activities cannot be optimally solved within a reasonable amount of time. Therefore heuristics employing...

This paper is devoted to a comparison of all available branch-and-bound algorithms that can be applied to solve resource-constrained project scheduling problems with multiple execution modes for each activity. After summarizing the two exact algorithms that have been suggested in the literature,...

In this paper we consider the resource-constrained project scheduling problem with multiple execution modes for each activity and makespan minimization as objective. We present a new genetic algorithm approach to solve this problem. The genetic encoding is based on a precedence feasible sequence...