Dynamic lot-sizing with rework of defective items and minimum lot-size constraints

Goerler, Andreas; Voß, Stefan

doi:10.1080/00207543.2015.1070970

Cited by 16 publications

(7 citation statements)

References 29 publications

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“…As a positive rework inventory at the end of the planning horizon is allowed for feasibility reasons any positive amount of defectives stored in the rework inventory or incurred in the last micro-period of the planning horizon (m j,m = L T ) has to be disposed, leading to disposal costs that are included in the last term of the objective function. Equations (12) and (13) present the production process of defectives as described in [49]. Concerning the planned lot size amount y j,m of a given micro-period m, only the reduced amount of y S j,m is of serviceable quality and can be used for demand satisfaction.…”

Section: Parameters H R Jmentioning

confidence: 99%

Late Acceptance Hill-Climbing Matheuristic for the General Lot Sizing and Scheduling Problem with Rich Constraints

2020

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This paper considers the general lot sizing and scheduling problem with rich constraints exemplified by means of rework and lifetime constraints for defective items (GLSP-RP), which finds numerous applications in industrial settings, for example, the food processing industry and the pharmaceutical industry. To address this problem, we propose the Late Acceptance Hill-climbing Matheuristic (LAHCM) as a novel solution framework that exploits and integrates the late acceptance hill climbing algorithm and exact approaches for speeding up the solution process in comparison to solving the problem by means of a general solver. The computational results show the benefits of incorporating exact approaches within the LAHCM template leading to high-quality solutions within short computational times.

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Section: Parameters H R Jmentioning

confidence: 99%

Late Acceptance Hill-Climbing Matheuristic for the General Lot Sizing and Scheduling Problem with Rich Constraints

2020

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“…Park and Klabjan [36] consider the single-item DLS problem with MOQ and devise the algorithm to solve the problem by defining the valid inequalities for the associated convex hull. Goerler and Voß [26] consider a capacitated DLS model with rework of defective items and minimum production quantities. Based on detailed numerical experiments, they give several managerial insights.…”

Section: Fuying Jing Zirui Lan and Yang Panmentioning

confidence: 99%

Forecast horizon of dynamic lot size model for perishable inventory with minimum order quantities

Jing¹,

Lan²,

Yang³

2020

Journal of Industrial &Amp; Management Optimization

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We consider the dynamic lot size problem for perishable inventory under minimum order quantities. The stock deterioration rates and inventory costs depend on both the age of the stocks and their periods of order. Based on two structural properties of the optimal solution, we develop a dynamic programming algorithm to solve the problem without backlogging. We also extend the model by considering backlogging. By establishing the regeneration set, we give a sufficient condition for obtaining forecast horizon under without and with backlogging. Finally, based on a detailed test bed of instance, we obtain useful managerial insights on the impact of minimum order quantities and perishability of product and the costs on the length of forecast horizon.

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“…Numerical examples were offered to show the results' applicability and sensitivity analyses on system performances with/without inspection policy. Goerler and Voß (2016) used a mixed-integer programming approach to explore the capacitated batch-size problem with defective products and rework processes. Various numerical experiments were performed to explore the influences of changes in defective instances on the required computer times for obtaining the optimal batch-size solutions.…”

Section: Introductionmentioning

confidence: 99%

Optimal hybrid inventory replenishment runtime for a vendor- buyer coordinated system with breakdowns and rework/disposal of nonconforming items

Chiu

Sung

2020

JART

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Most multinational/transnational manufacturers that own internal supply chains and operate in turbulent world markets apply strategies related to product quality, low-cost, and timely delivery. This study aims to assist such firms with making accurate decisions to enable their competitive strategies and cope with the realities of limited capacity and unreliable equipment. We examine a vendor-buyer coordinated system featuring batch fabrication, outsourcing, quality reassurance, discontinuous deliveries, and an unreliable machine. The system outsources a portion of a lot to reduce manufacturing uptime, and the in-house fabrication system experiences undesirable defective items and Poisson distributed breakdowns. In each cycle, corrective action and rework/disposal of defective stocks are undertaken as these incidents occur, and upon receipt of outsourced products and when the entire batch is quality ensured, it makes multiple deliveries of the end products. Using modeling, formulation, derivation, and an optimization methodology, we obtain the problem’s cost function and justify its convexity. We then apply differential calculus and propose a recursive algorithm to derive the problem’s optimal replenishment runtime. A numerical illustration is offered to show the applicability of the result that reveals various important system characteristics/ capabilities, such as the distinct and combined influences of breakdowns, outsourcing, rework, scrap, and delivery-frequency factors on various system parameters, performance, and optimal runtime. The methods proposed here can facilitate managerial operations planning and strategic decision making in an intra-supply chain setting in practice.

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Dynamic lot-sizing with rework of defective items and minimum lot-size constraints

Cited by 16 publications

References 29 publications

Late Acceptance Hill-Climbing Matheuristic for the General Lot Sizing and Scheduling Problem with Rich Constraints

Late Acceptance Hill-Climbing Matheuristic for the General Lot Sizing and Scheduling Problem with Rich Constraints

Forecast horizon of dynamic lot size model for perishable inventory with minimum order quantities

Optimal hybrid inventory replenishment runtime for a vendor- buyer coordinated system with breakdowns and rework/disposal of nonconforming items

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