ga algorithm

Choosing construction methods and how resources are allocated are important in the project control. The multi-mode resource constrained project scheduling problem (MRCPSP) is a significant subject in project management. The development of the above model for construction projects is an important issue because of uncertainty. Fuzzy logic has been used to display the uncertainty in the duration of activities and the delay between them. This paper examines this problem and schedules project with providing an intelligent algorithm combining fuzzy sets and genetic algorithms (GAs). The Fuzzy MRCPSP problem can be considered as the scheduling of a set of activities with the aim of finding an activity operation mode and the activity operation priority; so that the resource constraints (renewable resources and non-renewable resources) as well as the precedence constraints are met simultaneously and the time for completion of the project is minimal. In the first step, the above problem is modeled mathematically, and then the model is coded using GA-based algorithm in Matlab software and finally the model is solved. The results of the implementation of this algorithm on the standard instances of the PSPLIB site, in comparison with the GAMS software, indicate the successful performance of the combined GA algorithm with fuzzy sets. The approach used in this research can be easily used by project managers. This prevents human errors caused by people who are responsible for controlling the project at resource leveling phase and is a way to the optimized project scheduling.

Due to the growing traffic problem in cities, and serious need to develop a network of road transport infrastructure in the country as one of the major economic development, building bridges seems to be an imperative need. In this research, designing two element bridges (Concrete slab and steel carrier beam) has been represented as an optimization standard problem. The final weight of the bridge deck is considered as the goal function that is composed of concrete slab weight and beam weight. Designing constraints in this problem include limitations to design concrete slab such as stress limitation in slab transverse bars and the norms of longitudinal bars and necessary limitation for designing steel area section such as slimming constraint ingredients, limitations of longitudinal stiffener, constraint of compression stiffener, limitation of cutters, stress limitation of beam section and constraint of bridge deformation. This problem consists of 22 design variables and 39 constraints. The important issue in this problem is that all of the constraints are in accordance with the AASHTO regulation agreement and journal 395 (instruction to design steel bridges). CSS and GA algorithms are used for optimization and the performances of these two algorithms in solving the problem are compared with each others. In performance of algorithms, the power to access the best result and time to solve the problem is considered. Comparison is done by using Rank sum test statistical hypothesis and t test statistical hypothesis.