... module that utilizes genetic algorithms to search for and identify optimal crew deployment plans that provide optimal trade-offs between project duration and crew deployment plan cost. Findings A real-life example of street renovation is analyzed to illustrate the use of the model and demonstrate its...

...) with probabilistic and continuous rating approach for condition states. The M&RPPI uses a new approach of “dynamic” Markov chain to represent the deterioration mechanism of an infrastructure and the impact of rehabilitation interventions on such infrastructure. It also uses genetic algorithm (GA) in conjunction...

...Thomas K.L. Tong; C.M. Tam Multi‐skilled labour allocation in a defined time frame falls into the class of non‐polynomial (NP) hard problems, solutions to which can only be obtained through repeated trials and errors. The application of fuzzy genetic algorithms (GA) optimisation model provides...

... the function optimization problem, there still exists the need for improved solution techniques in solving the combinatorial optimization. This paper reports an exploratory work that investigates the integration of genetic algorithms (GAs) with organizational databases to solve the combinatorial problem...

...SHAMIL NAOUM; ALI HAIDAR This paper describes the development of a hybrid knowledge base system and genetic algorithms to select the optimum excavating and haulage equipment in opencast mining. The knowledge base system selects the equipment in broad categories based on the geological, technical...

...HASHEM AL‐TABTABAI; ALEX P. ALEX Genetic algorithm (GA) is a model of machine learning. The algorithm can be used to find sub‐optimum, if not optimum, solution(s) to a particular problem. It explores the solution space in an intelligent manner to evolve better solutions. The algorithm does not need...