Hybrid flow shop scheduling considering machine electricity consumption cost

Luo, Hao; Du, Benni; Huang, George Q.; Chen, Huaping; Li, Xiaolin

doi:10.1016/j.ijpe.2013.01.028

Cited by 311 publications

(102 citation statements)

References 56 publications

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“…Three bi-objective optimization methods based on SA developed to solve scheduling problem. Luo et al [21] studied a bi-objective HFS scheduling problem with uniform parallel machines from a new aspect of energy efficiency. In order to solve this problem, an ACO meta-heuristic applied to optimize both makespan and electric power cost with the presence of time-of-use electricity prices.…”

Section: Literature Reviewmentioning

confidence: 99%

Bi-objective scheduling for re-entrant hybrid flow shop with learning effect and setup times

et al. 2017

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The production scheduling problem in hybrid flow shops is a complex combinatorial optimization problem observed in many real-world applications. The standard hybrid flow shop problem involves often unrealistic assumptions. In order to address the realistic assumptions, four additional traits were added to the proposed problem. These include re-entrant line, setup times, position-dependent learning effects, and the consideration of maximum completion time together with total tardiness as objective function. Since the proposed problem is non-deterministic polynomial-time (NP)-hard, a meta-heuristic algorithm is proposed as the solution procedure. The solution procedure is categorized as an a priori approach. To show the efficiency and effectiveness of the proposed algorithm, computational experiments were done on various test problems. Computational results show that the proposed algorithm can obtain an effective and appropriate solution quality for our investigated problem.

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Section: Literature Reviewmentioning

confidence: 99%

Bi-objective scheduling for re-entrant hybrid flow shop with learning effect and setup times

et al. 2017

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“…The goal is to find the start time of each activity. Luo et al [22] proposed a new ant colony optimization for solving a hybrid flow shop scheduling problem taking into account machine electricity consumption cost.…”

Section: Literature Reviewmentioning

confidence: 99%

A new model and metaheuristic approach for the energy-based resource-constrained scheduling problem

Morillo-Torres

Barber

Salido

2017

Proceedings of the Institution of Mechanical Engineers, Part B:

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SAGE PublicationsMorillo-Torres, D.; Barber, F.; Salido, MA. (2017) instance, through a realistic mathematical model. This extension provides an alternative to the current trend of numerous researches about optimization and the manufacturing field, which require the inclusion of components to reduce the environmental impact in the decision-making process. PSPLIB-ENERGY is available at http://gps.webs.upv.es/psplib-energy/..

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“…Electricity cost and makespan are jointly minimized by a hybrid flow shop scheduling approach in [14]. The solution is encoded as a permutation of jobs.…”

Section: B Energy-cost-aware Production Schedulingmentioning

confidence: 99%

“…Based on the above philosophy, some energy-cost-aware production scheduling approaches can be found in literature [12][13][14][15][16][17][18]. Almost all these approaches emerged in the very recent years.…”

Section: Introductionmentioning

confidence: 99%

A power data driven energy-cost-aware production scheduling method for sustainable manufacturing at the unit process level

Gong

Pessemier

Joseph

et al. 2016

2016 IEEE 21st International Conference on Emerging Technologies and Factory Automation (ETFA)

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Abstract-Nowadays, the energy price is rising. The consciousness of environmental sustainability of governments and customers has been ever increasing. Consequently, manufacturing enterprises are increasingly motivated to reduce the energy cost involved in their production activities. This paper proposes a novel production scheduling method to minimize the energy cost involved in the production at the unit process level. Compared to the emerging energy-conscious production scheduling methods, this method builds the finite state machine based energy model from power data that are measured from the shop floor. By following the formulated mixed integer linear programming model, the power states and changeovers of a unit process can be additionally scheduled, and the potential multiple process idle modes can be optimally selected between two jobs. In addition, the process power consumption behavior can be predicted along with the optimal schedule. This method was demonstrated in an extrusion blow molding process in a Belgian plastic bottle manufacturer. Compared to two conventional schedules, i.e., "as-early-as-possible" and "as-late-as-possible", the schedule given by the proposed method is able to reduce 21% and 11% of electricity cost for completing the same production task before a due date.

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Hybrid flow shop scheduling considering machine electricity consumption cost

Cited by 311 publications

References 56 publications

Bi-objective scheduling for re-entrant hybrid flow shop with learning effect and setup times

Bi-objective scheduling for re-entrant hybrid flow shop with learning effect and setup times

A new model and metaheuristic approach for the energy-based resource-constrained scheduling problem

A power data driven energy-cost-aware production scheduling method for sustainable manufacturing at the unit process level

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