Scatter search based particle swarm optimization algorithm for earliness/tardiness flowshop scheduling with uncertainty

Geng, Jia-Can; Cui, Zhe; Gu, Xingsheng

doi:10.1007/s11633-016-0964-8

Cited by 16 publications

(5 citation statements)

References 24 publications

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“…The meta-heuristics algorithms combine an iterative procedure with strategies for exploring search space to produce feasible solutions (Ismail and Halim, 2017). Scatter search builds system solutions from a subset of the reference set and can combine with a tabu search to generate quality solutions (Geng et al , 2016). It also examines the multi-objective of a complex system with less computer time, unlike the other meta-heuristics (Amaran et al , 2016).…”

Section: Resultsmentioning

confidence: 99%

Construction project planning and scheduling as a dynamic system: a content analysis of the current status, technologies and forward action

Nwadigo

Naismith

Ghaffarianhoseini

et al. 2021

SASBE

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PurposeDynamic planning and scheduling forms a widely adopted smart strategy for solving real-world problems in diverse business systems. This paper uses deductive content analysis to explore secondary data from previous studies in dynamic planning and scheduling to draw conclusions on its current status, forward action and research needs in construction management.Design/methodology/approachThe authors searched academic databases using planning and scheduling keywords without a periodic setting. This research collected secondary data from the database to draw an objective comparison of categories and conclusions about how the data relates to planning and scheduling to avoid the subjective responses from questionnaires and interviews. Then, applying inclusion and exclusion criteria, we selected one hundred and four articles. Finally, the study used a seven-step deductive content analysis to develop the categorisation matrix and sub-themes for describing the dynamic planning and scheduling categories. The authors used deductive analysis because of the secondary data and categories comparison. Using the event types represented in a quadrant mapping, authors delve into where, when, application and benefits of the classes.FindingsThe content analysis showed that all the accounts and descriptions of dynamic planning and scheduling are identifiable in an extensive research database. The content analysis reveals the need for multi-hybrid (4D BIM-Agent based-discrete event-discrete rate-system dynamics) simulation modelling and optimisation method for proffering solutions to scheduling and planning problems, its current status, tools and obstacles.Originality/valueThis research reveals the deductive content analysis talent in construction research. It also draws direction, focuses and raises a question on dynamic planning and scheduling research concerning the five-integrated model, an opportunity for their integration, models combined attributes and insight into its solution viability in construction.

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Section: Resultsmentioning

confidence: 99%

Construction project planning and scheduling as a dynamic system: a content analysis of the current status, technologies and forward action

Nwadigo

Naismith

Ghaffarianhoseini

et al. 2021

SASBE

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“…MSS outperformed the exiting techniques in terms of accuracy. Geng et al [69] incorporated PSO in SS to minimize the earliness and tardiness constraints of FSP. DE was also used to produce the quality solutions in SS.…”

Section: Scheduling Naderi and Ruizmentioning

confidence: 99%

A Comprehensive Review on Scatter Search: Techniques, Applications, and Challenges

Kalra

Yadav

Kumar

et al. 2021

Mathematical Problems in Engineering

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Recent years have witnessed the use of metaheuristic algorithms to solve the optimization problems that usually require extensive computations and time. Among others, scatter search is the widely used evolutionary metaheuristic algorithm. It uses the information of global optima, which is stored in a different and unique set of solutions. In this paper, an updated review of scatter search (SS) is given. SS has been successfully applied in a variety of research problems, namely, data mining, bioinformatics, and engineering design. This paper presents the modified and hybrid versions of SS with their applications. The control strategies are discussed to show their impact on the performance of SS. various issues and future directions related to SS are also discussed. It inspires innovative researchers to use this algorithm for their research domains.

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“…In response to the above problems, a fast solution algorithm based on the improved particle swarm optimization (PSO) algorithm is proposed. The PSO algorithm [21] is a kind of intelligent searching algorithm, which can obtain the optimal or suboptimal solution in a short time.…”

Section: Solution Algorithm Of Multi-sensor Scheduling Problemmentioning

confidence: 99%

Multi-Sensor Optimization Scheduling for Target Tracking Based on PCRLB and a Novel Intercept Probability Factor

Pang

Duan

et al. 2019

Electronics

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In order to improve the survivability of active sensors, the problem of low probability of intercept (LPI) for a multi-sensor network system is studied in this paper. Two kinds of operational requirements are taken into account, the first of which is to ensure the survivability of sensors and the second is to improve the tracking accuracy of targets as much as possible. Firstly, the sensor tracking model and the posterior Carmér-Rao lower bound (PCRLB) of the target are presented to evaluate the sensor tracking benefits in next time. Then, a novel intercept probability factor (IPF) is proposed for multi-sensor multi-target tracking scenarios. At the basis of PCRLB and IPF, a myopic multi-sensor scheduling model for target tracking is set up to control the intercepted probability of sensors and improve the target tracking accuracy. At last, a fast solution algorithm based on an improved particle swarm optimization (PSO) algorithm is given to obtain the optimal scheduling actions. Simulation of experimental results show that the proposed model can effectively control the intercepted risk of every sensor, which can also obtain better target tracking performance than existing multi-sensor scheduling methods. of 22tracking accuracy, the survivability of sensor network should also be considered. It requires us to study new sensor scheduling methods considering both target tracking accuracy and battlefield survivability.Currently, there are four existing methods for active sensors to counter anti-radiation weapons: LPI waveform design technology [6][7][8], bistatic and distributed sensor technology [9,10], decoy and jamming technology [11], and sensor management technology [12][13][14]. Among them, the sensor management technology works through the cooperative work of multiple sensors. To realize the low intercepted probability of sensors, the key idea of sensor management technology is dynamically managing the existing sensor resources. It gives anti-radiation weapons difficulty in identifying the sensor or tracking the sensor for a long, continuous time. In this way, the anti-radiation weapon will not be able to position sensors or attack sensors further. This technology can reduce the intercepted probability of active sensors without increasing the hardware cost, which has become a research hotspot in this field. Reference [13] proposed a LPI controlling method based on Bhattacharyya distance and Jeffreys divergence, which can effectively control the intercepted risk of the whole radar network by reasonably allocating the radar working power. In [14], a low interception probability control method for multi-sensor networks based on mutual information entropy was presented. In [15,16], the radiation degree is used to quantify the intercepted risk of sensors. The radiation risk and the tracking accuracy are considered by information fusion method. However, combination of radiation risk and tracking precision is a single index. It is difficult to ensure that both of them can reach the ideal value. Secondly, the selection...

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Scatter search based particle swarm optimization algorithm for earliness/tardiness flowshop scheduling with uncertainty

Cited by 16 publications

References 24 publications

Construction project planning and scheduling as a dynamic system: a content analysis of the current status, technologies and forward action

Construction project planning and scheduling as a dynamic system: a content analysis of the current status, technologies and forward action

A Comprehensive Review on Scatter Search: Techniques, Applications, and Challenges

Multi-Sensor Optimization Scheduling for Target Tracking Based on PCRLB and a Novel Intercept Probability Factor

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