Capacity acquisition for the single-item lot sizing problem under energy constraints

Rapine, Christophe; Penz, Bernard; Gicquel, Céline; Akbalιk, Ayşe

doi:10.1016/j.omega.2017.10.004

Cited by 19 publications

(13 citation statements)

References 39 publications

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“…The majority of the papers published in the domain of energy-efficient production planning consists in energyefficient machine scheduling problems (see Biel and Glock [2]). To the best of our knowledge, there are only a few studies in the literature coupling energy issues with discrete lot sizing problem: Masmoudi et al [12], Giglio et al [10], that we have already discussed, and Rapine et al [20]. As mentioned earlier, the problem studied in this paper consists in an extension of the energy lot sizing problem presented in Rapine et al [20].…”

Section: Literature Reviewmentioning

confidence: 92%

“…Contributions of the paper. Problem energy-LSP in a parallel production system was first introduced by Rapine et al [20]. They propose a very efficient O(T log T ) algorithm for a restricted version assuming that start-up costs are stationary and that only one activity (start-up or production) consumes energy.…”

Section: Introductionmentioning

confidence: 99%

“…Our approach is based on dynamic programming and provides an O(M 6 T 6 ) exact algorithm for the most general case studied in this paper. To the best of our knowledge, there is no other theoretical studies on this integrated lot sizing and energy issues, except [20].…”

Section: Introductionmentioning

confidence: 99%

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Energy-aware lot sizing problem: Complexity analysis and exact algorithms

Rapine

Goisque

Akbalιk

2018

International Journal of Production Economics

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The single-item lot sizing problem under a periodic energy limitation is considered in this paper. Identical and parallel capacitated machines constitute the production system, each one consuming a certain amount of energy when being switched on, when reserved, and when producing. We consider a cost for starting-up the machines, a reservation cost to keep the machines ready for production, in addition to classical lot sizing costs, such as, joint setup cost, unit production cost and unit holding cost, all being time-dependent. Besides the classical lot sizing decisions of how much and in which periods to produce, we have to decide the number of machines to switch on and to switch off in each period. We show that this problem is NP-hard even under restricted conditions. In contrast, assuming stationary energy parameters, we propose two polynomial time dynamic programming algorithms to solve the problem to optimality. The first algorithm is proposed for the case with null setup cost, null reservation cost and null reservation energy consumption, and runs in O(M 5 T 4) time, with M being the number of machines and T the number of periods. We show that we can extend this algorithm to solve the generalized version of the problem in time complexity O(M 6 T 6).

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Section: Literature Reviewmentioning

confidence: 92%

Section: Introductionmentioning

confidence: 99%

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Energy-aware lot sizing problem: Complexity analysis and exact algorithms

Rapine

Goisque

Akbalιk

2018

International Journal of Production Economics

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“…Lastly, the authors presented several recommendations regarding future research about lot-sizing techniques and models. One variation of the single-item lot size problem, the Energy-Lot Size Problem (Energy-LSP), where it is necessary to decide which resources to use and how much to produce when machines have a limit in terms of how much energy can be consumed, is presented in Rapine et al (2018).…”

Section: Lot-sizing Techniquesmentioning

confidence: 99%

Analysis of lot-sizing methods’ suitability for different manufacturing application scenarios oriented to MRP and JIT/Kanban environments

Florim

Dias

Santos

et al. 2019

BJO&PM

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Goal: The main goal of this research is to analyse the behaviour of a set of ten lot-sizing methods applied to different application scenarios, within the context of more traditional MRP-based manufacturing environments and on JIT/ Kanbans oriented ones. Design/Methodology/Approach: After an extended literature review, a quantitative research method is used to provide a comparative analysis on the performance of the lot-sizing methods under different simulated application scenarios, with variations in demand and peaks of seasonality. Moreover, a final summary provides the error deviations for lot-sizing methods regarding increases in demand variations and seasonality indexes. Results: The study analyses lot-sizing methods and discusses benefits and risks associated to its use in application scenarios marked by a considerable variation in demand or peaks in seasonality. Limitations of the investigation: As the application scenarios did not explore variations in the ordering and stock holding costs, further analysis including these kinds of variations is encouraged. Practical implications: The findings of this research enable the enhancement of the conscience of industrial practitioners, regarding the selection of best suited lot-sizing methods for being applied on each kind of manufacturing scenario, regarding MRP or JIT/ Kanban environments. Originality/Value: Given the diversity of the existing lot-sizing methods, for instance, the heuristic ones, authors can find it quite difficult to select appropriate methods for solving their problems for each kind of application scenario. Therefore, the present study can provide useful knowledge to better support decision making in the lot-sizing domain.

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“…A comprehensive review of energy efficient production planning was provided by Biel and Glock [9]. Economic lot sizing problem with the energy consumption aspects was investigated by Rapine et al [11], whereas energy efficient manufacturing process chains was discussed by Mousavi et al [12]. Recently, González-Romera et al [13] investigated the renewable energy consumption for smart community under consumer comfort level considerations.…”

Section: Introductionmentioning

confidence: 99%

Economic Analysis of an Integrated Production–Inventory System under Stochastic Production Capacity and Energy Consumption

2019

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Expensive power cost is a significant concern in today’s manufacturing world. Reduction in energy consumption is an ultimate measure towards achieving manufacturing efficiency and emissions control. In the existing literature of scheduling problems, the consumption of energy is considered uncertain under the dimensions of uncertain demand and supply. In reality, it is a random parameter that also depends on production capacity, manufacturing technology, and operational condition of the manufacturing system. As the unit production cost varies with production rate and reliability of the manufacturing system, the energy consumption of the system also varies accordingly. Therefore, this study investigated an unreliable manufacturing system under stochastic production capacities and energy consumption. A stochastic production–inventory policy is developed to optimize production quantity, production rate, and manufacturing reliability under variable energy consumption costs. As energy consumption varies in different operational states of manufacturing, we consider three specific states of power consumption, namely working, idle, and repair time, for an integrated production–maintenance model. The considered production system is subjected to stochastic failure and repair time, where productivity and manufacturing reliability is improved through additional technology investment. The robustness of the model is shown through numerical example, comparative study, and sensitivity analysis of model parameters. Several graphical illustrations are also provided to obtain meaningful managerial insights.

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Capacity acquisition for the single-item lot sizing problem under energy constraints

Abstract: International audienc

Cited by 19 publications

References 39 publications

Energy-aware lot sizing problem: Complexity analysis and exact algorithms

Energy-aware lot sizing problem: Complexity analysis and exact algorithms

Analysis of lot-sizing methods’ suitability for different manufacturing application scenarios oriented to MRP and JIT/Kanban environments

Economic Analysis of an Integrated Production–Inventory System under Stochastic Production Capacity and Energy Consumption

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