Resolving Design Conflicts and Evaluating Solidarity in Distributed Design

被引:12
作者
Canbaz, Baris [1 ]
Yannou, Bernard [1 ]
Yvars, Pierre-Alain [2 ]
机构
[1] Ecole Cent Paris, Lab Genie Ind, Ind Engn Lab, F-92295 Chatenay Malabry, France
[2] French Ecole Cent Lille, F-59651 Villeneuve Dascq, France
来源
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS | 2014年 / 44卷 / 08期
关键词
Concurrent engineering; conflict resolution; constraint satisfaction problem; distributed design; multiagent systems; set-based design; MULTIATTRIBUTE NEGOTIATION; RESOLUTION; OPTIMIZATION; UNCERTAINTY; SYSTEM;
D O I
10.1109/TSMC.2013.2296275
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The resolution of complex design problems requires a distributed design system that considers the involvement of various designers. Inconsistencies of design objectives and working procedures of distributed subsystems can cause design conflicts due to couplings among their subproblems. Another issue is the management of imprecision in design systems caused by the lack of knowledge about the final decision. In this paper, we define a conflict management model using the concept of set-based design to overcome these issues. We utilize constraint satisfaction problem (CSP) techniques and model agent attitudes to detect and justify design conflicts of heterogeneous design agents. A novel cooperative CSP is defined for resolving design conflicts through compromising constraint restriction. The conflict resolution system can be adopted with different strategies which take into account the solidarity architecture of design agents. The gains and costs of centralized, decentralized and controlled conflict resolution system strategies are simulated with the Monte Carlo method where design agent characters and their interactions reflect a stochastic nature.
引用
收藏
页码:1044 / 1055
页数:12
相关论文
共 43 条
[1]   Fuzzy Preferences in the Graph Model for Conflict Resolution [J].
Abul Bashar, M. ;
Kilgour, D. Marc ;
Hipel, Keith W. .
IEEE TRANSACTIONS ON FUZZY SYSTEMS, 2012, 20 (04) :760-770
[2]   IMPRECISION IN ENGINEERING DESIGN [J].
ANTONSSON, EK ;
OTTO, KN .
JOURNAL OF MECHANICAL DESIGN, 1995, 117 :25-32
[3]  
Bratman M. E., 1988, Computational Intelligence, V4, P349, DOI 10.1111/j.1467-8640.1988.tb00284.x
[4]  
Canbaz B, 2014, PROCEEDINGS OF THE ASME INTERNATIONAL DESIGN ENGINEERING TECHNICAL CONFERENCES AND COMPUTERS AND INFORMATION IN ENGINEERING CONFERENCE, 2013, VOL 3A
[5]   Personality traits and social attitudes in multiagent cooperation [J].
Castelfranchi, C ;
de Rosis, F ;
Falcone, R ;
Pizzutilo, S .
APPLIED ARTIFICIAL INTELLIGENCE, 1998, 12 (7-8) :649-675
[6]  
Dechter R., 1988, AAAI 88. Seventh National Conference on Artificial Intelligence, P37
[7]   Introduction: Special issue on distributed constraint satisfaction [J].
Faltings, B ;
Yokoo, M .
ARTIFICIAL INTELLIGENCE, 2005, 161 (1-2) :1-5
[8]   Attitude based teams in a hostile dynamic world [J].
Goyal, M .
KNOWLEDGE-BASED SYSTEMS, 2005, 18 (06) :245-255
[9]  
Granvilliers Laurent, 2012, Principles and Practice of Constraint Programming. Proceedings 18th International Conference, CP 2012, P290, DOI 10.1007/978-3-642-33558-7_23
[10]  
Guo YT, 2003, LECT NOTES ARTIF INT, V2691, P303