In this paper we try to introduce the Ant Colony Optimization (ACO) and its application in Economic Dispatch ED). In the step one we present theory and performance of ant colony and its history and its application in various applications and how work the ant colony algorithm. In step two we present ant colony optimization include Basic Concept, Ant Searching Behavior, Path Retracing and Pheromo...

In an emergency situation (e.g., tsunami, chemical spill, fire) it may be necessary to displace people to safer locations. Evacuation plans must be prepared so that these movements are properly organized. Based on the ACO (ant colony optimization) meta-heuristic we design a computational model to optimize a multi-objective path-finding associated to an evacuation planning problem. The results a...

Ant systems are flexible to implement and give possibility to scale because they are based on multi agent cooperation. The aim of this publication is to show the universal character of that solution and potentiality in implementing it in wide areas of applications. The increase of demand for effective methods of large document collections management is a sufficient stimulus to place the researc...

Due to the inventions in technology, Wireless sensor networks have been growing rapidly. Sensor nodes are capable of performing some processing, gathering required information and communicating with other connected nodes in the network. Sensor nodes are of limited energy which is a drawback during peak times in a network. Always energy is of primary concern in a wireless sensor networks. There ...

In this paper we analyze the application of the Ant Colony Optimization to the Minimum Weight Vertex Covering Problem. We use the software system that we developed and implemented different standard ACO algorithms to this problem: Ant Colony System, the use of Elitism, Rank based approach and the MinMax system. We have made a comparative assessment of the effectiveness of these algorithms to th...

Many practically relevant problems have several objectives to be maximized or minimized, taking us into the area of Multiple Objective Optimization (MOO). In multi-objective optimization several conflicting objectives have to be simultaneously optimized. Therefore, there is usually no single solution which would give the best values for all the objective functions considered by the decision mak...

Ant colony algorithms are computational methods for solving problems that are inspired by the behaviour of real ant colonies. One particularly interesting aspect of the behaviour of ant colonies is that relatively simple individuals perform complicated tasks. Examples for such collective behavior are: i) the foraging behaviour that guides ants on short paths to their food sources, ii) the colle...

Inventory routing problems arise as simultaneous decisions in inventory and routing optimization. In the present study, vendor managed inventory is proposed as a collaborative model for reverse supply chains and the optimization problem is modeled in terms of an inventory routing problem. The studied reverse supply chains include several return generators and recovery centers and one collection...

Many practically relevant problems have several objectives to be maximized or minimized, taking us into the area of Multiple Objective Optimization (MOO). In multi-objective optimization several conflicting objectives have to be simultaneously optimized. Therefore, there is usually no single solution which would give the best values for all the objective functions considered by the decision mak...

In design and fabricate drive shafts with high value of fundamental natural frequency that represented high value of critical speed; using composite materials instead of typical metallic materials could provide longer length shafts with lighter weight. In this paper, multi-objective optimization (MOP) of a composite drive shaft is performed considering three conflicting objectives: fundamental ...