A Genetic Regulatory Network-Based Method for Dynamic Hybrid Flow Shop Scheduling with Uncertain Processing Times

Lv, Youlong; Zhang, Jie; Qin, Wei

doi:10.3390/app7010023

Cited by 7 publications

(3 citation statements)

References 44 publications

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“…This approach enables to respond to problems related to inventory management, production planning, scheduling, location of plants, among others (Chand et al 2002). The use of rolling horizons helps to relax large problems by decomposing them into smaller planning units (Garcia-Sabater et al 2009;Lv et al 2017;Ramezanian et al 2017;Rodriguez et al 2017;Zulkafli and Kopanos 2017). It should be noted that optimal approaches for each horizon act as heuristics and cannot guarantee that the proposed solution is optimum (Karimi et al 2003).…”

Section: Introductionmentioning

confidence: 99%

Operations planning test bed under rolling horizons, multiproduct, multiechelon, multiprocess for capacitated production planning modelling with strokes

Rius-Sorolla

Maheut

Miguel

et al. 2020

Cent Eur J Oper Res

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One of the problems when conducting research in mathematical programming models for operations planning is having an adequate database of experiments that can be used to verify advances and developments with enough factors to understand different consequences. This paper presents a test bed generator and instances database for a rolling horizons analysis for multiechelon planning, multiproduct with alternatives processes, multistroke, multicapacity with different stochastic demand patterns to be used with a stroke-like bill of materials considering production costs, setup, storage and delays for operations management. From the analysis of the operations planning obtained from this test bed, it is concluded that a product structure with an alternative process obtains the lowest total cost and the highest service level. In addition, decreasing seasonal demand could present a lower total cost than constant demand, but would generate a worse service level. This test bed will allow researchers further investigation so as to verify improvements in forecast methods, rolling horizons parameters, employed software, etc.

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Section: Introductionmentioning

confidence: 99%

Operations planning test bed under rolling horizons, multiproduct, multiechelon, multiprocess for capacitated production planning modelling with strokes

Rius-Sorolla

Maheut

Miguel

et al. 2020

Cent Eur J Oper Res

View full text Add to dashboard Cite

show abstract

“…A branch and price algorithm was applied to solve the model. Lv et al [21] proposed a novel method to solve the shop scheduling problem featured with uncertain processing times. Shan et al [22] utilized the Markov property and neural network ensemble to construct an estimated matrix that combines the interaction of the different local factors.…”

Section: Introductionmentioning

confidence: 99%

A Network-Based Method for the EMU Train High-Level Maintenance Planning Problem

Lin

Liu

2017

Applied Sciences

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Electric Multiple Unit (EMU) high-level maintenance planning is a typical discrete system. EMU high-level maintenance (HM) planning determines when to undergo HM or execute transportation task for train-sets, based on practical requirements such as passenger transport demand, workshop maintenance capacity, and maintenance regulations. This research constructs a time-state network that can display the transformation processes between different states. On this basis, a path based model and its improvement are developed to minimize the HM costs with consideration of all necessary regulations and practical constraints. To handle the solution space, a path set generation method is presented. A real-world instance from Shanghai Railway, which is the largest affiliate in China Railway Corporation, was conducted to demonstrate the efficiency and effectiveness of the proposed approach, which indicates that the model can be solved to optimum within short computational times by the state-of-the-art solver Gurobi. Moreover, a sensitivity analysis was also performed to evaluate the effects of the variation in average daily operating mileage, HM capacity at the depot and the assumed minimum value of cumulative mileage.

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“…The last paper [25], by Lv, Zhang, and Qin, deals with dynamic hybrid flow shop scheduling with uncertain processing time by proposing a genetic regulatory network-based rescheduling algorithm. The decision variables are represented by genes in the network and the constraints and certain rescheduling rules are described by regulation equations among genes.…”

mentioning

confidence: 99%

Special Issue on Modeling, Simulation, Operation and Control of Discrete Event Systems

Zhou

et al. 2018

Applied Sciences

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Information and computer technologies provide the spur to burgeoning man-made, highly automated systems. Nowadays, discrete event systems (DES), as a natural abstraction of various contemporary technological applications, include intelligent urban traffic systems, automated flexible manufacturing systems, computer networks, communication protocols, logistic systems, monitoring and control of large buildings, scientific and business workflows, distributed databases, and concurrent software systems. Their modeling, simulation, operation, scheduling and control are the primary issues to be investigated. It is of paramount significance to develop novel formal frameworks, analysis techniques, design tools, testing methods, and systematic control and optimization procedures for these kinds of man-made, highly complex systems. This is critical for their development and survivability [1][2][3][4][5][6].Focusing on supervisory control, deadlock analysis, scheduling, resource management, performance evaluation, system identification, fault diagnosis, and performance evaluation, as well as pertinent problems of DES, this special issue aims to make a timely collection of recent advances in the area. There were 77 manuscripts submitted to this special issue, and 19 papers were finally accepted for publication. The acceptance rate was 24.6%.The first paper [7], authored by Yao and Li, investigates the input-output finite time stabilization of time-varying impulsive positive hybrid systems based on finite state machines through the mode-dependent average dwell time technique. An output feedback controller is proposed that can stabilize non-autonomous hybrid systems by formulating the considered problem as a linear program. The second paper [8], authored by Yang, Peng, Ju, Xu, Yin, and Huang, is concerned with the efficiency improvement of multi-agent simulation. To address the problem of resynchronization interval selection and cyclic dependency, this paper presents a lookahead behavior model where a minimal safe time window is used to predict the interactions among implicit models. Consequently, the resynchronization interval can be efficiently determined.The third paper [9], authored by Kucharska, proposes a heuristic decision-making approach for an NP-hard scheduling problem based on an algebraic-logical meta-model. By constructing an acceptable solution only, it significantly reduces the calculation cost. A general algorithm is developed and applied to the scheduling problems of unrelated parallel machines with a deadline and machine setup time dependent on the process state. The fourth paper [10], authored by Choi, Seo, and Kim, deals with discrete event system simulation, aiming to improve simulation efficiency by using a multi-fidelity modeling framework, while keeping simulation accuracy loss minimized. A number of novel concepts, such as an interest region, a fidelity change condition, and a selection model, are defined and integrated into the framework.

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A Genetic Regulatory Network-Based Method for Dynamic Hybrid Flow Shop Scheduling with Uncertain Processing Times

Cited by 7 publications

References 44 publications

Operations planning test bed under rolling horizons, multiproduct, multiechelon, multiprocess for capacitated production planning modelling with strokes

Operations planning test bed under rolling horizons, multiproduct, multiechelon, multiprocess for capacitated production planning modelling with strokes

A Network-Based Method for the EMU Train High-Level Maintenance Planning Problem

Special Issue on Modeling, Simulation, Operation and Control of Discrete Event Systems

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