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A Cross-Entropy Based Population Learning Algorithm for multi-mode resource-constrained project scheduling Problem with Minimum and Maximum Time Lags

A Cross-Entropy Based Population Learning Algorithm for Mult...

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2nd International Conference on Computational Collective Intelligence: Technologies and Applications

作者： Jedrzejowicz, Piotr Skakovski, Aleksander Gdynia Maritime Univ Chair Informat Syst Ul Morska 83F PL-81225 Gdynia Poland Gdynia Maritime Univ Dept Navigat PL-81225 Gdynia Poland

ISBN: (纸本)9783642166921

The multi-mode resource-constrained project scheduling problem with minimum and maximum time lags is considered in the paper. An activity is performed in a mode, which determines the demand of renewable and nonrenewable resources required for its processing and minimum and maximum time lags between adjacent activities. The goal is to find a mode assignment to the activities and their start times such that all constraints are satisfied and the project duration is minimized. Because the problem is NP-hard a population-learning algorithm (PLA2) is proposed to tackle the problem. PLA2 is a population-based approach which takes advantage of the features common to the social education system rather than to the evolutionary processes. The proposed approach perfectly suits for multi-agent systems because it is based on the idea of constructing a hybrid algorithm integrating different optimization techniques complementing each other and producing a synergetic effect. Results of the experiment were compared to the results published in project scheduling Problem Library.

关键词： multi-mode resource-constrained project scheduling minimum and maximum time lags evolutionary computation population learning algorithm

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A Hybrid Method for the multi-mode resource-constrained project scheduling Problem with Strip Packing like resource Constraints

A Hybrid Method for the Multi-Mode Resource-Constrained Proj...

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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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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 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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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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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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Properties of multi-mode resource-constrained project scheduling problems with resource vacations and activity splitting

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EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2006年第1期175卷 279-295页

作者： Buddhakulsomsiri, Jirachai Kim, David S. Thammasat Univ Sch Mfg Syst & Mech Engn Sirindhorn Int Inst Technol Pathum Thani 12121 Thailand Oregon State Univ Dept Ind & Mfg Engn Corvallis OR 97331 USA

This paper presents results from an extensive computational study of the multi-mode resource-con strained project scheduling problem when activities can be split during scheduling under situations where resources may be temporarily not available. All resources considered are renewable and each resource unit may not be available at all times due to resource vacations, which are known in advance, and assignment to other finite duration activities. A designed experiment is conducted that investigates project makespan improvement when activity splitting is permitted in various project scenarios, where different project scenarios are defined by parameters that have been used in the research literature. A branch-and-bound procedure is applied to solve a number of small project scheduling problems with and without activity splitting. The results show that, in the presence of resource vacations and temporary resource unavailability, activity splitting can significantly improve the optimal project makespan in many scenarios, and that the makespan improvement is primarily dependent on those parameters that impact resource utilization. (c) 2005 Elsevier B.V. All rights reserved.

关键词： multi-mode resource-constrained project scheduling activity splitting time-varying resource capacities branch-and-bound

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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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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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