An agent-based simulation system for multi-project scheduling under uncertainty

Song, Wen; Xi, Hui; Kang, Dong‐Hun; Zhang, Jie

doi:10.1016/j.simpat.2018.05.009

Cited by 35 publications

(17 citation statements)

References 36 publications

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“…Ivanov [40] studied the impact of disruption propagation in light of the ripple effect in multi-stage supply chains. Song et al [41] developed an agent-based simulation system to support multi-project scheduling and decision-making processes. Unfortunately, numerous simulations implicate significant computational time and effort due to the high mathematical complexity of real-life problem descriptions.…”

Section: Related Workmentioning

confidence: 99%

Continuous Genetic Algorithms in the Optimization of Logistic Networks: Applicability Assessment and Tuning

Ignaciuk

Wieczorek

2020

Applied Sciences

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Globalization opens up new perspectives for handling goods distribution in logistic networks. However, establishing an efficient inventory policy is challenging by virtue of the analytical and computational complexity. In this study, the goods distribution process that was governed by the order-up-to policy, implemented in either a distributed or centralized way, was investigated in the logistic systems with complex interconnection topologies. Uncertain demand may be imposed at any node, not just at conveniently chosen contact points, with a lost-sales assumption that introduces a non-linearity into the node dynamics. In order to adjust the policy parameters, the continuous genetic algorithm (CGA) was applied, with the fitness function incorporating both the operational costs and customer satisfaction level. This study investigated how to select the parameters of the popular inventory management policy when operating in the non-trivial networked structures. Moreover, precise guidelines for the CGA tuning in the considered class of problems were provided and evaluated in extensive numerical experiments.

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Section: Related Workmentioning

confidence: 99%

Continuous Genetic Algorithms in the Optimization of Logistic Networks: Applicability Assessment and Tuning

Ignaciuk

Wieczorek

2020

Applied Sciences

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“…Only a few pieces of research dealt with the uncertainty in the distributed RCMPSP. For instance, Song et al [34] assumed that the uncertainty of activity duration is related to the starting time, and the fault statistics of the instruments. If the number of faulty instruments reaches a certain limit, the corresponding activity is failed.…”

Section: Literature Reviewmentioning

confidence: 99%

A Multi-PR Heuristic for Distributed Multi-Project Scheduling With Uncertain Duration

Liu

2020

IEEE Access

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“…Recently, the RCMPSP was addressed again in an article published by Song et al [42]. In this research work, the authors proposed a simulation model based on agents and applied to a new product development program.…”

Section: A Relevant Literature Review For the Scheduling Problem In Npdpmentioning

confidence: 99%

An optimization model to solve the resource constrained project scheduling problem RCPSP in new product development projects•

Pimiento

Serna

2020

DYNA

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New product development projects (NPDP) face different risks that may affect the scheduling. In this article, the purpose was to develop an optimization model to solve the RCPSP in NPDP and obtain a robust baseline for the project. The proposed model includes three stages: the identification of the project’s risks, an estimation of activities’ duration, and the resolution of an integer linear program. Two versions of the model were designed and compared in order to select the best one. The first version uses a method to estimate the activities’ duration based on the expected value of the impact of the risks and the second version uses a method based on the judgmental risk analysis process. Finally, the two version of the model were applied to a case study and the best version of the model was identified using a robustness indicator that analyses the start times of the baselines generated.

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An agent-based simulation system for multi-project scheduling under uncertainty

Cited by 35 publications

References 36 publications

Continuous Genetic Algorithms in the Optimization of Logistic Networks: Applicability Assessment and Tuning

Continuous Genetic Algorithms in the Optimization of Logistic Networks: Applicability Assessment and Tuning

A Multi-PR Heuristic for Distributed Multi-Project Scheduling With Uncertain Duration

An optimization model to solve the resource constrained project scheduling problem RCPSP in new product development projects•

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