A parallel-machine scheduling with periodic constraints under uncertainty

Shen, Jiayu; Zhu, Yuanguo

doi:10.1177/1687814019892430

Cited by 2 publications

(2 citation statements)

References 30 publications

(30 reference statements)

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“…Mokotoff et al (2001) introduced a list scheduling algorithm to solve the scheduling problem of minimizing the makespan on identical machines. Shen and Zhu (2019) designed an improved LPT algorithm to solve the uncertainties and stochastic events, such as machine breakdowns, during job scheduling. Furthermore, job scheduling always encounters multiple objectives in practice; thus, numerous multi-objective approaches have been established.…”

Section: Parallel Machine Scheduling Problemmentioning

confidence: 99%

Operation design of a robot logistics system considering demand fluctuations in the hotel industry

Gu¹,

Liao²

2023

IJCHM

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Purpose The purpose of this paper is to consider three factors, namely, intra-week demand fluctuations, interrelationship between the number of robots and order scheduling and conflicting objectives (i.e. cost minimization and customer satisfaction maximization), to optimize the robot logistics system. Design/methodology/approach The number of robots and the sequence of delivery orders are first optimized using the heuristic algorithm NSGACoDEM, which is designed using genetic algorithm and composite difference evolution. The superiority of this method is then confirmed by a case study of a four-star grade hotel in South Korea and several comparative experiments. Findings Two performance metrics reveal the superior performance of the proposed approach compared to other baseline approaches. Results of comparative experiments found that the consideration of three influencing factors in the operation design of a robot logistic system can effectively balance cost and customer satisfaction over the course of a week in hotel operation and optimize robot scheduling flexibility. Practical implications The results of this study reveal that numerous factors (e.g. intra-week demand fluctuations) can optimize the performance efficiency of robots. The proposed algorithm can be used by hotels to overcome the influence of intra-week demand fluctuations on robot scheduling flexibility effectively and thereby enhance work efficiency. Originality/value The design of a novel algorithm in this study entails enhancing the current robot logistics system. This algorithm can successfully manage cost and customer satisfaction during off-seasons and peak seasons in the hotel industry while offering diversified schemes to various types of hotels.

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Section: Parallel Machine Scheduling Problemmentioning

confidence: 99%

Operation design of a robot logistics system considering demand fluctuations in the hotel industry

Gu¹,

Liao²

2023

IJCHM

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“…Actually, some abnormal events happen in actual production, such as additional roller grinding task and the breakdown of the grinding machine, causing the numbers of the rollers to be processed and the available grinding machines. 38 Also, the time of grinding or cooling process is not always certain in some circumstances. Considering the cases above, the position sensors are fixed on the roller positions of the processing zones, and the temperature sensors are also fixed on the roller positions of the cooling zone.…”

Section: Further Analysismentioning

confidence: 99%

The study of intelligent scheduling algorithm oriented to complex constraints and multi-process roller grinding workshop

Wang

Jiang³

et al. 2014

Advances in Mechanical Engineering

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Roller grinding workshop is a typical multi-unit and multi-task manufacturing scenario, which is aimed to repair the surface damage of the rollers caused by the rolling process, so that the rollers can be reused. Due to the process complexity of roller grinding workshop and the large volume and weight of the roller, hoisting and transportation mode with multiple cranes is required. Consequently, the scheduling of the roller grinding workshop needs to consider both the task sequencing in time and the noninterference of the multi-crane trajectory in space. In this paper, the intelligent scheduling of roller grinding workshop is studied based on the characteristics of complex tasks and space-time coupling constraints. Firstly, the scheduling basis is established based on priority rules and process constraints. In order to solve the scheduling problem under the space-time coupling constraints, the position coordinate system is established, and then the algorithms of crane position tracking and cooperative motion without interference are developed. Further, considering the transportation time of crane and its out of sync time point with the processes, the intelligent decision and scheduling algorithm are developed based on the dynamic priority strategy defined to realize scheduling, including time decision, crane decision, and process decision. With the developed intelligent scheduling algorithm applied, the simulation of the roller grinding workshop is conducted under three combinations of priority strategy and noninterference strategy to verify algorithm performance. Under the guarantee of crane noninterference during the full production, the efficiency is improved by 22.1% compared with the existing processing mode of industry. Additionally, EPTR (effective process time rate) based on dynamic priority strategy and noninterference strategy B is up to 100% to avoid intervals between two processes in the scheduling. The dynamic priority developed in this paper reveals more efficiency than MOR principle, while with the strategy B the CUR (crane utilization rate) can be improved more than 20% under the condition of enough machines which facilitates to obtain shorter makespan than strategy A. The intelligent scheduling algorithm developed guarantees the effectiveness and rationality of scheduling with multi-unit and multi-task under the complex constraints. Finally, in order to realize the automatic and intelligent operation of the roller grinding workshop, the management software of the roller grinding workshop is developed by integrating the intelligent scheduling algorithm, which realizes the intelligent production, monitoring, and management of the roller grinding workshop during the full production cycle.

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A parallel-machine scheduling with periodic constraints under uncertainty

Cited by 2 publications

References 30 publications

Operation design of a robot logistics system considering demand fluctuations in the hotel industry

Operation design of a robot logistics system considering demand fluctuations in the hotel industry

The study of intelligent scheduling algorithm oriented to complex constraints and multi-process roller grinding workshop

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