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 addresses methods for formulating and solving a general class of nonpreemptive resource-constrained project scheduling problems in which job durations are discrete functions of committed renewable, nonrenewable and doubly-constrained resources (multi-mode time resource tradeoff). We...