Ant colony optimization for resource-constrained project scheduling
نویسندگان
چکیده
منابع مشابه
Ant Colony Optimization for Resource-Constrained Project Scheduling
An ant colony optimization approach (ACO) for the resource-constrained project scheduling problem (RCPSP) is presented. Combinations of two pheromone evaluation methods are used by the ants to find new solutions. We tested our ACO algorithm on a set of large benchmark problems from the PSPLIB. Compared to several other heuristics for the RCPSP including genetic algorithms, simulated annealing, ...
متن کاملAnt Colony Optimization for Resource-Constrained Projet Scheduling
An ant colony optimization (ACO) approach for the resource-constrained project scheduling problem (RCPSP) is presented. Several new features that are interesting for ACO in general are proposed and evaluated. In particular, the use of a combination of two pheromone evaluation methods by the ants to find new solutions, a change of the influence of the heuristic on the decisions of the ants durin...
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In this paper Hybrid Ant Colony Optimization (HAntCO) approach in solving Multi–Skill Resource Constrained Project Scheduling Problem (MS–RCPSP) has been presented. We have proposed hybrid approach that links classical heuristic priority rules for project scheduling with Ant Colony Optimization (ACO). Furthermore, a novel approach for updating pheromone value has been proposed, based on both th...
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resource constraints project scheduling problem (rspsp) seeks proper sequence of implementation of project activities in a way that the precedence relations and different type of resource constraints are met concurrently. rcpsp tends to optimize some measurement function as make-span, cost of implementation, number of tardy tasks and etc. as rcpsp is assumed as an np-hard problem so, different ...
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The extraction of comprehensible knowledge is one of the major challenges in many domains. In this concept, an ant programming (AP) framework, which is capable of mining classification rules easily comprehensible by humans, and, therefore, capable of supporting expert-domain decisions, is presented. The algorithm proposed, called grammar based ant programming (GBAP), is the first AP algorithm d...
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ژورنال
عنوان ژورنال: IEEE Transactions on Evolutionary Computation
سال: 2002
ISSN: 1089-778X
DOI: 10.1109/tevc.2002.802450