Christine Strauss

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The ant system is a new meta-heuristic for hard combinatorial optimization problems. It is a population-based approach that uses exploitation of positive feedback as well as greedy search. It was rst proposed for tackling the well known Traveling Salesman Problem (TSP), but has been also successfully applied to problems such as quadratic assignment,(More)
In this paper we use a recently proposed metaheuristic, the Ant System, to solve the Vehicle Routing Problem (VRP) in its basic form, i.e. with capacity and distance restrictions, one central depot and identical vehicles. A \hybrid" Ant System algorithm is rst presented and then improved using problem speciic information (savings, capacity utilization).(More)
The content and qualities of a good software requirements specification (SRS) are described and several sample SRS outlines are presented. This recommended practice is aimed at specifying requirements of software to be developed but also can be applied to assist in the selection of in-house and commercial software products. Guidelines for compliance with(More)
Ant Colony Optimization is a relatively new meta-heuristic that has proven its quality and versatility on various combinatorial optimization problems such as the traveling salesman problem, the vehicle routing problem and the job shop scheduling problem. The paper introduces an Ant Colony Optimization approach to solve the problem of determining a(More)
The Ant System is a new meta-heuristic method particularly appropriate to solve hard combinatorial optimization problems. It is a populationbased, nature-inspired approach exploiting positive feedback as well as local information and has been applied successfully to a variety of combinatorial optimization problem classes. The Ant System consists of a set of(More)
One of the most important, common and critical management issues lies in determining the “best” project portfolio out of a given set of investment proposals. As this decision process usually involves the pursuit of multiple objectives amid a lack of a priori preference information, its quality can be improved by implementing a two-phase procedure that first(More)
Ant Colony Optimization is a relatively new meta-heuristic that has proven its quality and versatility on various combinatorial optimization problems such as the traveling salesman problem, the vehicle routing problem and the job shop scheduling problem. The paper introduces an Ant Colony Optimization approach to solve the problem of determining a(More)
In this paper we propose a hybrid approach for solving vehicle routing problems. The main idea is to combine an Ant System (AS) with a problem specific constructive heuristic, namely the well known Savings algorithm. This differs from previous approaches, where the subordinate heuristic was the Nearest Neighbor algorithm initially proposed for the TSP. We(More)