Evaluation of Agents Performance within the A-Team Solving RCPSP/Max Problem

In this paper the E-JABAT-based A-Team architecture dedicated for solving the RCPSP/max problem instances is proposed and experimentally validated. Computational experiment involves evaluation of agent performance within the A-Team. The paper contains the RCPSP/ max problem formulation, description of the E-JABAT architecture for solving the RCPSP/max problem instances and the discussion of the computational experiment results.

[1]  Ngoc Thanh Nguyen,et al.  Intelligent Agents in the Evolution of Web and Applications , 2009, Intelligent Agents in the Evolution of Web and Applications.

[2]  Stephen F. Smith,et al.  A Constraint-Based Method for Project Scheduling with Time Windows , 2002, J. Heuristics.

[3]  Piotr Jedrzejowicz,et al.  e-JABAT - An Implementation of the Web-Based A-Team , 2009, Intelligent Agents in the Evolution of Web and Applications.

[4]  Piotr Jedrzejowicz,et al.  JADE-Based A-Team Environment , 2006, International Conference on Computational Science.

[5]  Cândida Ferreira,et al.  Gene Expression Programming: Mathematical Modeling by an Artificial Intelligence (Studies in Computational Intelligence) , 2006 .

[6]  Jan Karel Lenstra,et al.  Scheduling subject to resource constraints: classification and complexity , 1983, Discret. Appl. Math..

[7]  Ewa Ratajczak-Ropel.  Experimental Evaluation of the A-Team Solving Instances of the RCPSP/max Problem , 2010, KES-AMSTA.

[8]  Rolf H. Möhring,et al.  Scheduling project networks with resource constraints and time windows , 1988 .

[9]  Candida Ferreira.  Gene expression programming , 2006 .

[10]  Piotr Jedrzejowicz,et al.  Solving the RCPSP/max Problem by the Team of Agents , 2009, KES-AMSTA.

[11]  Piotr Jedrzejowicz,et al.  Agent-Based Approach to Solving the Resource Constrained Project Scheduling Problem , 2007, ICANNGA.

[12]  Joanna Józefowska,et al.  Perspectives in modern project scheduling , 2006 .

[13]  Professor Dr. Klaus Neumann,et al.  Project Scheduling with Time Windows and Scarce Resources , 2003, Springer Berlin Heidelberg.

[14]  Cândida Ferreira,et al.  Gene Expression Programming: Mathematical Modeling by an Artificial Intelligence , 2014, Studies in Computational Intelligence.

[15]  Piotr Jedrzejowicz,et al.  Agent-Based Gene Expression Programming for Solving the RCPSP/max Problem , 2009, ICANNGA.

[16]  Klaus Neumann,et al.  Resource-Constrained Project Scheduling with Time Windows , 2006 .

[17]  Sarosh Talukdar,et al.  Asynchronous teams : cooperation schemes for autonomous, computer-based agents , 1996 .

[18]  Jan Wessnitzer,et al.  A Model of Non-elemental Associative Learning in the Mushroom Body Neuropil of the Insect Brain , 2007, ICANNGA.

[19]  Stephen Gilmore,et al.  Combining Measurement and Stochastic Modelling to Enhance Scheduling Decisions for a Parallel Mean Value Analysis Algorithm , 2006, International Conference on Computational Science.