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7th International Conference on Engineering Computational Technology

作者： Szendroi, E. Univ Pecs Pecs Hungary

ISBN: (纸本)9781905088416

This paper presents an improved hybrid algorithm for the multi-mode resource-constrained project scheduling problem with strip packing like resource constraints. In the proposed primary-secondary criteria algorithm, a resource-constrained project is characterized by its "best" schedule, where best means a makespan minimal resource-constrained schedule with dedicated resource demand servicing for which the resource profiles approach the ideal rectangular shape as much as possible. In the traditional resource-constrained project scheduling the activities are not necessarily assigned to the same resource units over their processing times, so an "optimal" solution may be far from the reality, because the machine (workforce) changing always needs extra time and cost. In the improved model the activities are assigned to dedicated resource units over their processing times. The applied resource leveling-smoothing procedure, preferring the continuous work, tries to minimize the number of starting-restarting events of dedicated resource units on the set of resource-feasible activity movements fixing the makespan, the modes, and the scheduling order. To illustrate the essence and viability of the proposed approach, we present detailed computational results for a medium size project instance.

关键词： multi-mode resource-constrained project scheduling heuristic and metaheuristic techniques harmony search optimization hybrid methods resource leveling strip packing

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A Heuristic Genetic Algorithm for multi-mode resource-constrained project scheduling Problem

A Heuristic Genetic Algorithm for Multi-Mode Resource-Constr...

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2010 3rd IEEE International Conference on Computer Science and Information Technology—ICCSIT 2010

作者： Li Zheng 1 Qin Jinlei 2 Zhang Changming 1 1.Department of Computer Science and Technology North China Electric Power University (Baoding) Baoding,China 2.Information and Network Management Center North China Electric Power University (Baoding) Baoding,China

A heuristic genetic algorithm for multi-mode resource-constrained project scheduling problem is given because the requisition of constraints of using renewable and nonrenewable resource in practical engineering is taken into *** of nonrenewable resource,weighted coefficient and the duration are combined,and objective function is constructed dynamically by choosing different *** this way,the optimal solution of scheduling mode can be gained which meets different needs of *** has been proved that by adopting the algorithm,not only duration can be the shortest,but also nonrenewable resources can be saved maximum,which will be great significance to achieve the optimal arrangement of time and resources in practical production.

关键词： heuristic genetic algorithm weight multi-mode resource-constrained project scheduling scheduling pattern sequence

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Robust decision trees for the multi-mode project scheduling problem with a resource investment objective and uncertain activity duration

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EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2024年第2期312卷 525-540页

作者： Portoleau, Tom Artigues, Christian Guillaume, Romain Univ Toulouse CNRS LAAS 7 Ave Colonel Roche F-31031 Toulouse 4 France Univ Toulouse CNRS IRIT 118 Route Narbonne F-31062 Toulouse 9 France

In this paper, we advocate the use of robust decision trees for a multi-mode resource constrained project scheduling problem with uncertain activity duration and a resource investment objective, coming from an industrial assembly line scheduling application. This work takes place in the context of multi-stage optimization where uncertainty is revealed progressively across a succession of decision time points. In a robust decision tree, a node represents a robust partial schedule from the time origin to a specific decision time point. At this point, the decision maker has access to some information, which partitions the uncertainty scenario set, yielding for each scenario subset a child node and an associated extended partial robust schedule up to the next decision point. Considering that the level of uncertainty is lowered, the new partial schedule is less conservative and improves the robustness guarantee. However, since all accessible information may not be relevant, we turned the information selection part into an optimization problem. An algorithm is proposed to solve the robust decision tree problem. Experimentation is provided to study the influence of decision tree parameters as well as highlighted recommendations. The interest of the decision tree is shown through an experimental comparison with classical approaches of the literature on benchmark instances and industrial instances.

关键词： scheduling multi-mode resource-constrained project scheduling resource investment multistage robust optimization Decision trees

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On the generalization of constraint programming and boolean satisfiability solving techniques to schedule a resource-constrained project consisting of multi-mode jobs

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OPERATIONS RESEARCH PERSPECTIVES 2017年 4卷 1-11页

作者： Schnell, Alexander Hartl, Richard F. Univ Vienna Dept Business Adm Chair Prod & Operat Management Oskar Morgenstern Pl 1 A-1090 Vienna Austria

In our paper, we analyze new exact approaches for the multi-mode resource-constrained project scheduling (MRCPSP) problem with the aim of makespan minimization. For the single-mode RCPSP (SRCPSP) recent exact algorithms combine a Branch and Bound algorithm with principles from Constraint Programming (CP) and Boolean Satisfiability Solving (SAT). We extend the above principles for the solution of MRCPSP instances. This generalization is on the one hand achieved on the modeling level. We propose three CP-based formulations of the MRCPSP for the G12 CP platform and the optimization framework SCIP which both provide solution techniques combining CP and SAT principles. For one of the latter we implemented a new global constraint for SCIP, which generalizes the domain propagation and explanation generation principles for renewable resources in the context of multi-mode jobs. Our constraint applies the above principles in a more general way than the existing global constraint in SCIP. We compare our approaches with the state-of-the-art exact algorithm from the literature on MRCPSP instances with 20 and 30 jobs. Our computational experiments show that we can outperform the latter approach on these instances. Furthermore, we are the first to close (find the optimal solution and prove its optimality for) 628 open instances with 50 and 100 jobs from the literature. In addition, we improve the best known lower bound of 2815 instances and the best known upper bound of 151 instances. (C) 2017 The Authors. Published by Elsevier Ltd.

关键词： multi-mode resource-constrained project scheduling Constraint programming SAT solving SCIP Lazy clause generation Exact algorithm

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A new proactive and reactive approach for resource-constrained project scheduling problem under activity and resource disruption: a scenario-based robust optimization approach

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ANNALS OF OPERATIONS RESEARCH 2024年第1期338卷 597-643页

作者： Khoshsirat, Maziar Mousavi, Seyed Meysam Shahed Univ Dept Ind Engn Tehran Iran

This paper introduces a novel two-phase framework for designing a proactive-reactive scheduling model in the multi-mode resource-constrained project scheduling problem under disruptions. The proactive phase involves constructing a resilient baseline scheduling model using a mixed-integer linear programming model. This phase contributes to a multi-objective model that minimizes the project completion time and total project cost while maximizing resilience criteria. In this context, resilience refers to allocating float time to project activities to protect their start and finish times against future disruptions as much as possible. The reactive phase involves a bi-objective mathematical model that mitigates the impact of disruptions through preempt-repeat, preempt-resume, and activity-crashing strategies. Real-world projects involve many uncertain parameters that can negatively affect the optimization of rescheduling problems if overlooked. Therefore, for the first time, a scenario-based robust optimization approach is proposed to cope with the uncertainty of the reactive phase. Additionally, a novel hybrid multi-objective method based on goal programming is introduced to solve the proposed multi-objective model. Finally, to demonstrate the capability of the proposed approach, an oil and gas project in Iran is regarded as a real case study. The results indicate that the negative impact of disruptions on the makespan and total cost of the project can be largely mitigated by considering resilience criteria in the proactive phase and preempt-repeat, preempt-resume, and activity-crashing strategies in the reactive phase.

关键词： multi-mode resource-constrained project scheduling Disruption Resiliency Proactive and reactive scheduling Scenario-based robust optimization Hybrid multi-objective method

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Double-Action Agents Solving the MRCPSP/Max Problem

Double-Action Agents Solving the MRCPSP/Max Problem

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3rd International Conference on Computational Collective Intelligence (ICCCI 2011)

作者： Jedrzejowicz, Piotr Ratajczak-Ropel, Ewa Gdynia Maritime Univ Dept Informat Syst PL-81225 Gdynia Poland

ISBN: (纸本)9783642239373;9783642239380

In this paper an A-Team architecture for solving the multi-mode resource-constrained project scheduling problem with minimal and maximal time lags (MRCPSP/max) is proposed and experimentally validated. To solve this problem an asynchronous team of agents implemented using JABAT middleware has been proposed. Four kinds of optimization agent has been used. Each of them acts in two ways depending whether the received initial solution is feasible or not. The paper contains the MRCPSP/max problem formulation, description of the proposed architecture for solving the problem instances, description of optimization algorithms, description of the experiment and the discussion of the computational experiment results.

关键词： project scheduling multi-mode resource-constrained project scheduling MRCPSP optimization agent agent system A-Team

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Reinforcement Learning Strategy for Solving the MRCPSP by a Team of Agents 7th

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7th KES International Conference on Intelligent Decision Technologies (KES-IDT)

作者： Jedrzejowicz, Piotr Ratajczak-Ropel, Ewa Gdynia Maritime Univ Chair Informat Syst Morska 83 PL-81225 Gdynia Poland

ISBN: (纸本)9783319198576;9783319198569

In this paper the strategy for the A-Team with Reinforcement Learning (RL) approach for solving the multi-mode resource-constrained project scheduling Problem (MRCPSP) is proposed and experimentally validated. The MRCPSP belongs to the NP-hard problem class. To solve this problem a team of asynchronous agents (A-Team) has been implemented using multiagent system. An A-Team is the set of objects including multiple agents and the common memory which through interactions produce solutions of optimization problems. These interactions are usually managed by the static strategy. In this paper the dynamic learning strategy is suggested. The proposed strategy based on reinforcement learning supervises interactions between optimization agents and the common memory. To validate the proposed approach computational experiment has been carried out.

关键词： multi-mode resource-constrained project scheduling MRCPSP Optimization Agent A-Team Reinforcement learning

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PLA Based Strategy for Solving MRCPSP by a Team of Agents 8th

PLA Based Strategy for Solving MRCPSP by a Team of Agents

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8th KES International Conference on Intelligent Decision Technologies (KES-IDT)

作者： Jedrzejowicz, Piotr Ratajczak-Ropel, Ewa Gdynia Maritime Univ Chair Informat Syst Morska 83 PL-81225 Gdynia Poland

ISBN: (纸本)9783319396309;9783319396293

In this paper the dynamic interaction strategy based on the Population Learning Algorithm (PLA) for the A-Team solving the multi-mode resource-constrained project scheduling Problem (MRCPSP) is proposed and experimentally validated. The MRCPSP belongs to the NP-hard problem class. To solve this problem a team of asynchronous agents (A-Team) has been implemented using multiagent system. An A-Team is the set of objects including multiple agents and the common memory which through interactions produce solutions of optimization problems. These interactions are usually managed by some static strategy. In this paper the dynamic learning strategy based on PLA is suggested. The proposed strategy supervises interactions between optimization agents and the common memory. To validate the proposed approach computational experiment has been carried out.

关键词： multi-mode resource-constrained project scheduling MRCPSP Optimization Agent A-team Population learning algorithm

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A-Team for Solving MRCPSP/max Problem

A-Team for Solving MRCPSP/max Problem

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5th KES International Conference on Agent and multi-Agent Systems - Technologies and Applications (KES-AMSTA)

作者： Jedrzejowicz, Piotr Ratajczak-Ropel, Ewa Gdynia Maritime Univ Dept Informat Syst PL-81225 Gdynia Poland

ISBN: (纸本)9783642219993;9783642220005

In this paper the E-JABAT-based A-Team architecture for solving multi-mode resource-constrained project scheduling problem with minimal and maximal time lags (MRCPSP/max) is proposed and experimentally validated. MRCPSP/max, also known as MRCPSP-GPR (MRCPSP with generalised precedence relations), belongs to the NP-hard problem class. To solve this problem an asynchronous team of agents implemented using JABAT middleware has been proposed. Three kinds of optimization agent has been used. Computational experiment involves evaluation of optimization agent performance within the A-Team. The paper contains the MRCPSP/max problem formulation, description of the proposed architecture for solving the problem instances, description of optimization algorithms and the discussion of the computational experiment results.

关键词： project scheduling multi-mode resource-constrained project scheduling MRCPSP optimization agent agent system A-Team

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