scholarly journals Finding an optimal Nash equilibrium to the multi-agent project scheduling problem

2017 ◽  
Vol 20 (5) ◽  
pp. 475-491 ◽  
Author(s):  
Cyril Briand ◽  
Sandra Ulrich Ngueveu ◽  
Přemysl Šůcha
Keyword(s):  
Nash Equilibrium ◽  
Project Scheduling ◽  
Scheduling Problem ◽  
Multi Agent ◽  
Project Scheduling Problem

A Multi-Agent Optimization Method for Preemptive Resource-Constrained Project Scheduling

2019 ◽  
Vol 10 (1) ◽  
pp. 21-33
Author(s):  
Yongyi Shou ◽  
Wenjin Hu ◽  
Changtao Lai ◽  
Ying Ying
Keyword(s):  
Project Scheduling ◽  
Optimization Method ◽  
Negotiation Process ◽  
Scheduling Problem ◽  
Scheduling Problems ◽  
Project Schedule ◽  
Resource Constrained ◽  
Resource Constrained Project Scheduling ◽  
Multi Agent ◽  
Project Scheduling Problem

A multi-agent optimization method is proposed to solve the preemptive resource-constrained project scheduling problem in which activities are allowed to be preempted no more than once. The proposed method involves a multi-agent system, a negotiation process, and two types of agents (activity agents and schedule agent). The activity agents and the schedule agent negotiate with each other to allocate resources and optimize the project schedule. Computational experiments were conducted using the standard project scheduling problem sets. Compared with prior studies, results of the proposed method are competitive in terms of project makespan. The method can be extended to other preemptive resource-constrained project scheduling problems.

scholarly journals A-Team Solving Distributed Resource-Constrained Multi-Project Scheduling Problem

2019 ◽  
Vol 06 (04) ◽  
pp. 423-437
Author(s):  
Piotr Jędrzejowicz ◽  
Ewa Ratajczak-Ropel
Keyword(s):  
Global Optimization ◽  
Project Scheduling ◽  
Optimization Problems ◽  
Global Solutions ◽  
Scheduling Problem ◽  
Multi Agent System ◽  
Resource Constrained ◽  
Agent System ◽  
Multi Agent ◽  
Project Scheduling Problem

In this paper, a multi-agent system (MAS) based on the A-Team concept is proposed to solve the Distributed Resource-Constrained Multi-Project Scheduling Problem (DRCMPSP). In the DRCMPSP, multiple distributed projects are considered. Hence, the local task schedule for each project and a coordination of the shared decisions are considered. The DRCMPSP belongs to the class of the strongly NP-hard optimization problems. Multi-agent system seems the natural way of solving such problems. The A-Team MAS, proposed in this paper, has been built using the JABAT environment where two types of the optimization agents are used: local and global. Local optimization agents are used to find solutions for the local projects, and global optimization agents are responsible for the coordination of the local projects and for finding the global solutions. The approach has been tested experimentally using 140 benchmark problem instances from MPSPLIB library with minimizing the Average Project Delay (APD) as global optimization criterion.

scholarly journals A multi-objective multi-agent optimization algorithm for the multi-skill resource-constrained project scheduling problem with transfer times

2021 ◽  
Author(s):  
Amirhossein Hosseinian ◽  
Vahid Baradaran
Keyword(s):  
Optimization Algorithm ◽  
Project Scheduling ◽  
Scheduling Problem ◽  
Resource Constrained ◽  
Resource Constrained Project Scheduling ◽  
Multi Objective ◽  
Proposed Model ◽  
Multi Agent ◽  
Project Scheduling Problem ◽  
Transfer Times

This paper addresses the Multi-Skill Resource-Constrained Project Scheduling Problem with Transfer Times (MSRCPSP-TT). A new model has been developed that incorporates the presence of transfer times within the multi-skill RCPSP. The proposed model aims to minimize project’s duration and cost, concurrently. The MSRCPSP-TT is an NP-hard problem; therefore, a Multi-Objective Multi-Agent Optimization Algorithm (MOMAOA) is proposed to acquire feasible schedules. In the proposed algorithm, each agent represents a feasible solution that works with other agents in a grouped environment. The agents evolve due to their social, autonomous, and self-learning behaviors. Moreover, the adjustment of environment helps the evolution of agents as well. Since the MSRCPSP-TT is a multi-objective optimization problem, the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) is used in different procedures of the MOMAOA. Another novelty of this paper is the application of TOPSIS in different procedures of the MOMAOA. These procedures are utilized for: (1) detecting the leader agent in each group, (2) detecting the global best leader agent, and (3) the global social behavior of the MOMAOA. The performance of the MOMAOA has been analyzed by solving several benchmark problems. The results of the MOMAOA have been validated through comparisons with three other meta-heuristics. The parameters of algorithms are determined by the Response Surface Methodology (RSM). The Kruskal-Wallis test is implemented to statistically analyze the efficiency of methods. Computational results reveal that the MOMAOA can beat the other three methods according to several testing metrics. Furthermore, the impact of transfer times on project’s duration and cost has been assessed. The investigations indicate that resource transfer times have significant impact on both objectives of the proposed model

scholarly journals Nash equilibria for the multi-agent project scheduling problem with controllable processing times

2014 ◽  
Vol 18 (1) ◽  
pp. 15-27 ◽  
Author(s):  
Alessandro Agnetis ◽  
Cyril Briand ◽  
Jean-Charles Billaut ◽  
Přemysl Šůcha
Keyword(s):  
Project Scheduling ◽  
Nash Equilibria ◽  
Controllable Processing Times ◽  
Scheduling Problem ◽  
Processing Times ◽  
Multi Agent ◽  
Project Scheduling Problem
Sign in / Sign up

Export Citation Format

Share Document