In project management, the project duration can often be compressed by accelerating some of its activities at an additional expense. This is the so-called time-cost tradeoff problem which has been extensively studied in the past. However, the discrete version of the problem which is of great...

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...

Over the years numerous branch-and-bound procedures for solving the resource-constrained project scheduling problem (RCPSP) have been developed. Enumerating delaying alternatives, extension alternatives, feasible posets, feasible sequences, feasible completion times or feasible subsets, they all...

Over the years numerous branch-and-bound procedures for solving the resource-constrained project scheduling problem have been developed. Enumerating delaying alternatives, extension alternatives, feasible posets, feasible sequences or feasible subsets, they all aim at finding as fast as possible...

Most scheduling problems are notoriously intractable, so the majority of algorithms for them are heuristic in nature. Priority rule-based methods still constitute the most important class of these heuristics. Of these, in turn, parameterized biased random sampling methods have attracted...

Most scheduling problems are notoriously intractable, so the majority of algorithms for them are heuristic in nature. Priority rule-based methods still constitute the most important class of these heuristics. Of these, in turn, parameterized biased random sampling methods have attracted...

For most computationally intractable problems there exists no heuristic which performs best on all instances. Usually, a heuristic characterized as best will perform good on the majority of instances but leave a minority on which other heuristics do better. In priority rule-based scheduling,...