Heuristic optimization through negotiation

Finding realistic and express solutions to several problems has been a fundamental requirement in this rapidly changing conditions and environment. Conventional approaches, which are solving dynamic problems, ?as they are static? or reinventing their models after each corresponding change, have all expired. In this respect, it has been understood that, the most effective solution strategies have been the agent-based strategies. These strategies, which are mostly constructed upon a heuristic, are capable to provide parallel and distributed solutions and furthermore they let agents to take autonomous decisions that can add value to the objectives of the problem. This PhD thesis aims both 1) setting up a representation scheme for agent-based approaches and 2) providing solutions to dynamic variants of Travelling Salesman Problem (TSP), which has been solved by static approaches up to now.Classical TSP consists of ?n number of cities? where, each city is visited once using an optimal route. Similarly, Generalized Travelling Salesman Problem (GTSP) covers ?c number clusters? where, each cluster is visited exactly once by visiting one of cities of the clusters using an optimal route. However, in some specific cases, assumptions of classical TSP and GTSP may not be satisfactorily enough to reflect physical reality and dynamism of actual systems. During solution of those problems, some cities are added to city domain or some disappear from the system. Thereby, the assumption of keeping the number of cities constant fails. Consequently, ?a solution provided for a specific to state defined for a time? may lose its superiority immediately after these unexpected changes. In this respect, these dynamic types of TSP and GTSP may not be modeled with the conventional research methods since much time and memory spaces are required to setup novel models and solve them repeatedly. With those considerations in mind, this thesis covers different agent-based solution policies/strategies for providing promising solutions to different problems in domain of dynamic TSP. In this respect, two main solution strategies are proposed for the solution of the defined problem types in this PhD thesis. One of these is competition of agents without a heuristic and the other is competition of agents using Great Deluge Algorithm (GDA). All those strategies have proved themselves competed with other findings in literature.