Multi-Objective Task Allocation Via Multi-Agent Coalition Formation

A Master of Science thesis in Engineering Systems Management by Noha Tarek Amer entitled, "Multi-Objective Task Allocation Via Multi-Agent Coalition Formation," submitted in May 2012. Thesis advisor is Dr. Fouad Ben Abdelaziz. Available are both soft and hard copies of the thesis.

محفوظ في:
التفاصيل البيبلوغرافية
المؤلف الرئيسي: Amer, Noha Tarek (author)
التنسيق: doctoralThesis
منشور في: 2012
الموضوعات:
الوصول للمادة أونلاين:http://hdl.handle.net/11073/4071
الوسوم: إضافة وسم
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author Amer, Noha Tarek
author_facet Amer, Noha Tarek
author_role author
dc.contributor.none.fl_str_mv Abdelaziz, Fouad Ben
dc.creator.none.fl_str_mv Amer, Noha Tarek
dc.date.none.fl_str_mv 2012-09-16T07:32:23Z
2012-09-16T07:32:23Z
2012-05
dc.format.none.fl_str_mv application/pdf
dc.identifier.none.fl_str_mv 35.232-2012.17
http://hdl.handle.net/11073/4071
dc.language.none.fl_str_mv en_US
dc.subject.none.fl_str_mv multi-objective programming
coalition formation
task allocation
genetic algorithms
cooperative agents
non-cooperative agents
Programming (Mathematics)
Multiagent systems
Mathematical models
dc.title.none.fl_str_mv Multi-Objective Task Allocation Via Multi-Agent Coalition Formation
dc.type.none.fl_str_mv info:eu-repo/semantics/publishedVersion
info:eu-repo/semantics/doctoralThesis
description A Master of Science thesis in Engineering Systems Management by Noha Tarek Amer entitled, "Multi-Objective Task Allocation Via Multi-Agent Coalition Formation," submitted in May 2012. Thesis advisor is Dr. Fouad Ben Abdelaziz. Available are both soft and hard copies of the thesis.
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spelling Multi-Objective Task Allocation Via Multi-Agent Coalition FormationAmer, Noha Tarekmulti-objective programmingcoalition formationtask allocationgenetic algorithmscooperative agentsnon-cooperative agentsProgramming (Mathematics)Multiagent systemsMathematical modelsA Master of Science thesis in Engineering Systems Management by Noha Tarek Amer entitled, "Multi-Objective Task Allocation Via Multi-Agent Coalition Formation," submitted in May 2012. Thesis advisor is Dr. Fouad Ben Abdelaziz. Available are both soft and hard copies of the thesis.Nowadays, tasks are complex and cannot be performed by individual agents. Therefore, there is a need to form coalitions utilizing the resources in order to maximize the efficiency of the system and/or maximize the payoff of each agent. In this thesis, we will formulate an optimization model to form optimal coalitions of agents satisfying both maximizing the efficiency of the system for cooperative settings and/or the payoff of the agent for non-cooperative settings. For small sized problems, we propose an optimization model to get exact solutions. For large sized problems, we propose genetic algorithms to get satisfying solutions. Different experiments were performed for the different settings. For cooperative settings, we observe that the tasks with the maximum payment are being performed, the agents who are most capable are assigned to perform the task provided they are the cheapest, and agents are assigned if and only if they will participate in performing a task to avoid any wasted costs. As for the genetic algorithms, the code is giving exact solution for medium problems. For selfish settings, we observe that the tasks with the maximum payments are being performed because they give maximum payoffs for agents, and agents prefer high payment over a complex task; that is, a capable agent would perform a high paying complex task rather than a low paying simple task. Also, very frequently all agents are assigned to tasks even if they don't contribute to accomplishing the task just to increase their payoff. As for the genetic algorithms, the code is giving exact solution for medium problems with time savings advantages. As for the hybrid setting, we observe that by comparing both cooperative and selfish agents, cooperative agents provide better results for the system. Our results coincide with the theories of game theory that say cooperative games provide a higher utility. However, we also show that combining both behaviors of agents, cooperative and selfish, provides better results. In addition to that, our genetic algorithm is giving exact solution for medium problems with time savings towards problems with a large number of agents. Most applications are realized in e-commerce systems or parallel processing. Search Terms: Multi Objective Programming, Coalition Formation, Task Allocation, Genetic Algorithms, Cooperative Agents, Non-Cooperative AgentsCollege of EngineeringDepartment of Industrial EngineeringMaster of Science in Engineering Systems Management (MSESM)Abdelaziz, Fouad Ben2012-09-16T07:32:23Z2012-09-16T07:32:23Z2012-05info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/doctoralThesisapplication/pdf35.232-2012.17http://hdl.handle.net/11073/4071en_USoai:repository.aus.edu:11073/40712025-06-26T12:15:42Z
spellingShingle Multi-Objective Task Allocation Via Multi-Agent Coalition Formation
Amer, Noha Tarek
multi-objective programming
coalition formation
task allocation
genetic algorithms
cooperative agents
non-cooperative agents
Programming (Mathematics)
Multiagent systems
Mathematical models
status_str publishedVersion
title Multi-Objective Task Allocation Via Multi-Agent Coalition Formation
title_full Multi-Objective Task Allocation Via Multi-Agent Coalition Formation
title_fullStr Multi-Objective Task Allocation Via Multi-Agent Coalition Formation
title_full_unstemmed Multi-Objective Task Allocation Via Multi-Agent Coalition Formation
title_short Multi-Objective Task Allocation Via Multi-Agent Coalition Formation
title_sort Multi-Objective Task Allocation Via Multi-Agent Coalition Formation
topic multi-objective programming
coalition formation
task allocation
genetic algorithms
cooperative agents
non-cooperative agents
Programming (Mathematics)
Multiagent systems
Mathematical models
url http://hdl.handle.net/11073/4071