Authors:
Houssem Eddine Nouri
;
Olfa Belkahla Driss
and
Khaled Ghédira
Affiliation:
Stratégies d'Optimisation et Informatique intelligentE, Tunisia
Keyword(s):
Scheduling, Transport, Robot, Genetic Algorithm, Tabu Search, Holonic Multiagent.
Related
Ontology
Subjects/Areas/Topics:
Agents
;
Artificial Intelligence
;
Artificial Intelligence and Decision Support Systems
;
Cognitive Robotics
;
Computational Intelligence
;
Distributed and Mobile Software Systems
;
Distributed Problem Solving
;
Enterprise Information Systems
;
Evolutionary Computing
;
Formal Methods
;
Hybrid Intelligent Systems
;
Industrial Applications of AI
;
Informatics in Control, Automation and Robotics
;
Intelligent Control Systems and Optimization
;
Knowledge Engineering and Ontology Development
;
Knowledge-Based Systems
;
Multi-Agent Systems
;
Planning and Scheduling
;
Robot and Multi-Robot Systems
;
Robotics and Automation
;
Simulation and Modeling
;
Soft Computing
;
Software Engineering
;
Symbolic Systems
Abstract:
In systems based robotic cells, the control of some elements such as transport robot has some difficulties when planning operations dynamically. The Job Shop scheduling Problem with Transportation times and a Single Robot (JSPT-SR) is a generalization of the classical Job Shop scheduling Problem (JSP) where a set of jobs additionally have to be transported between machines by a single transport robot. Hence, the JSPT-SR is more computationally difficult than the JSP presenting two NP-hard problems simultaneously: the job shop scheduling problem and the robot routing problem. This paper proposes a hybrid metaheuristic approach based on clustered holonic multiagent model for the JSPT-SR. Firstly, a scheduler agent applies a Neighborhood-based Genetic Algorithm (NGA) for a global exploration of the search space. Secondly, a set of cluster agents uses a tabu search technique to guide the research in promising regions. Computational results are presented using benchmark data instances fro
m the literature of JSPT-SR. New upper bounds are found, showing the effectiveness of the presented approach.
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