An adaptive immune algorithm based on the endocrine regulation mechanism for scheduling problems of flow shop with zero wait

Wang, Yi; Gu, Xing Sheng; Xu, Zhen

doi:10.1504/ijmic.2011.037828

Cited by 3 publications

(2 citation statements)

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“…Recently, tabu approach, immune algorithm, simulated annealing algorithm, genetic algorithms (GAs), particle swarm and hybrid algorithm et al are used to solve the HFSP problem (Tang and Wu, 2002;Li et al, 2003;Han et al, 2005;Cui et al, 2005;Zandieh et al, 2006;Zhang et al, 2009;Yang et al, 2010;Wang et al, 2011;Zhao et al, 2013). Differential evolution (DE) algorithm is one of the latest evolutionary optimization methods proposed by Storn and Price (1997).…”

Section: Introductionmentioning

confidence: 99%

Time-window-based combined objective DE algorithm for hybrid flow-shop

Han

Shi

Yao

2014

IJMIC

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Abstract:In this paper, a time-window-based hybrid flow-shop scheduling model is presented for manufacturing enterprise for solving production scheduling optimisation problem in the rolling production process. Time window deviation sum and the earliness/tardiness (E/T) penalty sum's optimisation goal are modelled, and differential evolution (DE) global optimisation algorithm is used to conduct the global optimisation. The assigned tasks to determine a job's machining path in the time window frame can be finished in each stage. The hybrid flow-shop scheduling optimisation method based on time window can improve the equipment utilisation and reduce scheduling conflict situations. Our time-window-based hybrid flow-shop scheduling optimisation method is evaluated by multiple sets of programs' numerical analysis, and the results show that the proposed approach can meet the requirement of business rolling production scheduling very well.

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Section: Introductionmentioning

confidence: 99%

Time-window-based combined objective DE algorithm for hybrid flow-shop

Han

Shi

Yao

2014

IJMIC

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“…Yang et al (2002) used BB algorithm to schedule a given set of independent jobs on a single machine to minimise the sum of early and tardy costs. Yau et al (2008) combined dynamic programming (DP) with BB algorithm to solve the general single-machine E/T problem and machine idle time was considered; Wang et al (2011) adopted an adaptive immune algorithm for scheduling problems of flow shop with zero wait; modified GA (Wang et al, 2006) and PSO (Lian et al, 2006) are also used to make solutions for E/T problem. Note that all of these studies aimed to solve the single-machine E/T problem with some restrictions (e.g., common due date, no idle machine time, equal E/T unit costs).…”

Section: Introductionmentioning

confidence: 99%

Multiple rules decision-based DE solution for the earliness-tardiness case of hybrid flow-shop scheduling problem

Han

Shi

Qiao

et al. 2012

IJMIC

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Abstract:The earliness/tardiness (E/T) case of hybrid flow-shop scheduling problem (HFSP) is an NP hard problem, which is difficult to deal with; however, the existence of the multi-rules relating to the practical production increases the complexity of this problem. How to solve the combinatorial optimisation problem effectively and optimally is still an open issue today. In this paper, the joint scheduling strategy of differential evolution (DE) algorithm and factor space-based multiple rules decision method is used to solve this E/T scheduling problem. Firstly, DE algorithm is used to make global assignment and obtain each job's process route. Secondly, factor space method is used to describe the scheduling rules in production process; then a scheduling decision method based on variable weight comprehensive function is considered to figure out the jobs' operating priority in buffer area during the local production assignment between stages; subsequently the starting time of each job can be determined. Finally, under the constraints of the due-date and multiple production rules, the global optimisation with the minimal penalty sum of E/T is obtained. Several scheme comparisons with experiment results show the effectiveness of the proposed method.

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