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...

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...

We consider the multi-mode resource-constrained project scheduling problem. The focus is on an algorithm which is supposed to find a makespan optimal solution. This algorithm has been presented in a recent paper by Speranza and Vercellis. The correctness of the algorithm is examined. Moreover,...

We consider an extension of the classical resource-constrained project scheduling problem (RCPSP), which covers discrete resource-resource and time-resource tradeoffs. As a result a project scheduler is permitted to identify several alternatives or modes of accomplishment for each activity of...

We consider the multi-mode resource-constrained project scheduling problem. The focus is on an algorithm which is supposed to find a makespan optimal solution. This algorithm has been presented in a recent paper by Speranza and Vercellis. The correctness of the algorithm is examined. Moreover,...

We consider an extension of the classical resource-constrained project scheduling problem (RCPSP), which covers discrete resource-resource and time-resource tradeoffs. As a result a project scheduler is permitted to identify several alternatives or modes of accomplishment for each activity of...