استفاده از الگوریتم بهینه سازی کلنی مورچگان برای حل مشکلات مدیریت پروژه

Network analysis provides an effective practical system for planning and controlling large projects in construction and many other fields. Ant Colony System is a recent approach used for solving path minimization problems. This paper presents the use of Ant Colony Optimization (ACO) system for solving and calculating both deterministic and probabilistic CPM/PERT networks. The proposed method is investigated for a selected case study in construction management. The results demonstrate that – compared to conventional methods – ACO can produce good optimal and suboptimal solutions.

Effective project management techniques are important to ensure successful project performance; a poor strategy can easily turn expected profit into loss. With the availability of computer facilities the design, calculation, modeling, managing and checking processes and projects can be done in a more efficient and effective manner. The management of construction project involves planning of tasks from large numbers of disciplines which require different pieces of information at various times. This results in the production of a huge quantity of complex information, which must be managed efficiently. Network analysis provides a comprehensive practical system for planning and controlling large projects in construction and many other fields. One of the most needed tasks is to accomplish a forecast of optimal and suboptimal paths of the network for construction management due to the complexity of the project and the possibility of crash or delay occurrence which is not so easy with conventional methods. The integration of optimization algorithms based on metaheuristic opens new perspectives of applications in real life. Ant Colony System has been introduced in the early 1990s. It mimics the performance of natural ants while searching food and finding the shortest path between the nest and the food source thanks to local message exchange (Bonabeau, Dorigo, & Theraulaz, 1999). This paper proposes the use of Ant Colony System to analyze PERT network problems to solve decision making problem in project management.

Several researchers have investigated the critical path analysis in the project network with fuzzy activity times, random time. This paper develops an approach to use Ant Colony Systems for solving both deterministic and probabilistic CPM/PERT networks. The applicability of the proposed algorithm is demonstrated for a typical construction project and another project with uncertain data. Investigation of the results reveals that the main advantage of the proposed method over traditional optimization algorithms is the ability of the Ant system to produce good optimal and suboptimal solutions. Other advantages of the proposed method can be marked. The proposed method can be easily applied to more complicated application in network analysis; like networks with uncertainty (random or fuzzy data), crash analysis in CPM network, etc. Finally the proposed method has introduced the power of ACO algorithm in computing and analyzing PERT networks.