Capacitated lot‐sizing and scheduling with parallel machines, back‐orders, and setup carry‐over

Quadt, Daniel; Kühn, Heinrich

doi:10.1002/nav.20345

Cited by 42 publications

(25 citation statements)

References 58 publications

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“…Only few researchers have addressed capacitated lot sizing problems with back-ordering Daniel Quadt, Heinrich Kuhn [11], also the complexity of the modeling setup carry over in CLSP problems result in the not much attention in the literatures [18]. So in this paper we consider a lot sizing and scheduling in flow shop with sequence-dependent setups, setups carry over and backlogging.…”

Section: Mathematical Modelmentioning

confidence: 99%

“…Equation (10) and (11) represent the relationship between successive setups. Equation (8) to (11) ensure that for each triple (n,m,t) there is exactly one pair (i,j) which ˳ ŵ. The type of variables is defined by equations (12) and (13) and finally equation (14) indicates that at the end of planning horizon there is no on-hand inventory.…”

Section: Formulationmentioning

confidence: 99%

“…Examples include the articles byDaniel Quadt, Heinrich Kuhn [11],Pochet and Wolsey [12], Millar and Yang [13], Karimi et al [15], and. In some cases demand cannot be backlogged, but will be totally or partially lost.…”

Section: Introductionmentioning

confidence: 99%

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Lot Sizing and Scheduling in Flow Shop with SequenceDependent Setups and Backlogging

Babaei¹,

Mohammadi²,

Ghomi³

2011

IJCA

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Lot sizing and scheduling in flow shop has been considered in this paper. Our study includes a multi-level and multi-period capacitated lot sizing and scheduling problem (CLSP) with sequence-dependent setups, setups carry over in flow shop. In manufacturing environments backlogging is unavoidable. If the production capacity is infinite, any demand can be satisfied on time. But in the real world, production capacity is not infinite so some demand may not be satisfied on time. In this condition backlogging arises naturally. CLSP problems with considering backlogging has been studied fewer by researchers. Also, the sequence-dependent setups and setups carry over are two important events that occur occasionally in factories. In this study an exact mixed integer problem (MIP) in a flow shop CLSP problem with considering sequence-dependent setups, setups carry over and backlogging has been formulated. Our formulation is presented to optimize objective function (including, inventory costs, product costs and setup cost). Since the CLSP problems are extremely NP-hard a lower bound is developed and compared against the optimal solution. General TermsLot sizing and Scheduling.

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Section: Mathematical Modelmentioning

confidence: 99%

Section: Formulationmentioning

confidence: 99%

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Lot Sizing and Scheduling in Flow Shop with SequenceDependent Setups and Backlogging

Babaei¹,

Mohammadi²,

Ghomi³

2011

IJCA

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“…We refer the interested readers to [3,4] for the most recent review on CLSPs. For the lot-sizing problems considering backlogging and setup carryovers jointly, models were treated in [5][6][7]. Their problem formulations were similar to [8], who first solved problems with setup carryovers.…”

Section: Introductionmentioning

confidence: 99%

Fix‐and‐Optimize and Variable Neighborhood Search Approaches for Stochastic Multi‐Item Capacitated Lot‐Sizing Problems

Song

et al. 2017

Mathematical Problems in Engineering

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We discuss stochastic multi-item capacitated lot-sizing problems with and without setup carryovers (also known as link lot size), S-MICLSP and S-MICLSP-L. The two models are motivated from a real-world steel enterprise. To overcome the nonlinearity of the models, a piecewise linear approximation method is proposed. We develop a new fix-and-optimize (FO) approach to solve the approximated models. Compared with the existing FO approach(es), our FO is based on the concept of " -degreeconnection" for decomposing the problems. Furthermore, we also propose an integrative approach combining our FO and variable neighborhood search (FO-VNS), which can improve the solution quality of our FO approach by diversifying the search space. Numerical experiments are performed on the instances following the nature of realistic steel products. Our approximation method is shown to be efficient. The results also show that the proposed FO and FO-VNS approaches significantly outperform the recent FO approaches, and the FO-VNS approaches can be more outstanding on the solution quality with moderate computational effort.

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“…However, the SLSSP model generally does not consider feasible production planning and scheduling conditions. In most studies, the production environment of a single machine, parallel machine and flow shop are studied in order to adjust the time and processing sequence [9][10][11].…”

Section: Introductionmentioning

confidence: 99%

Integrated Optimization Model for Production Planning and Scheduling with Logistics Constraints

Chen¹

2016

Int. j. simul. model.

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Production planning and the development of manufacturing production scheduling are two important operational management tasks. The results of these tasks will strongly influence the development of corporate profits, as well as the efficiency of utilization of resources. Considering the production scheduling problems in production plans can effectively avoid conflicts between the specific implementation production plan and the actual situations, and ultimately maximize resource utilization efficiency. This paper attempts to establish an integrated optimization model of production planning and scheduling with consideration of logistics constraints. A modified heuristic algorithm is proposed to solve this problem. In the final portion of this paper, a simulation analysis is given to demonstrate the outstanding advantage of the model and the algorithm, which gives further thought for the production planning.

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Capacitated lot‐sizing and scheduling with parallel machines, back‐orders, and setup carry‐over

Cited by 42 publications

References 58 publications

Lot Sizing and Scheduling in Flow Shop with SequenceDependent Setups and Backlogging

Lot Sizing and Scheduling in Flow Shop with SequenceDependent Setups and Backlogging

Fix‐and‐Optimize and Variable Neighborhood Search Approaches for Stochastic Multi‐Item Capacitated Lot‐Sizing Problems

Integrated Optimization Model for Production Planning and Scheduling with Logistics Constraints

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