Managing product variety with mixed make-to-stock/make-to-order production strategy and guaranteed delivery time under stochastic demand

•Study of Make-to-Stock & Make-to-Order items sharing facility and semi-finished goods.•Integrated management of inventory, and demand with guaranteed lead-time.•Analysis of conditions favoring mixed strategy/substitution among semi-finished goods.•Modification of cuts, search and branching stra...

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Bibliographic Details
Published in:	Computers & industrial engineering Vol. 147; p. 106603
Main Authors:	Kuthambalayan, Thyagaraj S., Bera, Samiran
Format:	Journal Article
Language:	English
Published:	Elsevier Ltd 01.09.2020
Subjects:	Guaranteed lead-time Make-to-Order Make-to-Stock Marketing/Operations interface Non-linear Branch & Bound method Stochastic 0–1 integer non-linear programming Non-linear Branch & Bound method Guaranteed lead-time Stochastic 0–1 integer non-linear programming Make-to-Stock Marketing/Operations interface Make-to-Order
ISSN:	0360-8352, 1879-0550
Online Access:	Get full text
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Summary:	•Study of Make-to-Stock & Make-to-Order items sharing facility and semi-finished goods.•Integrated management of inventory, and demand with guaranteed lead-time.•Analysis of conditions favoring mixed strategy/substitution among semi-finished goods.•Modification of cuts, search and branching strategy in Branch & Bound (B&B) method.•Solution of the stochastic 0–1 nonlinear programming problem with Greedy + B&B method. Firms often use a facility to produce both Make-to-Stock (MTS) and Make-to-Order (MTO) items. This study provides insights into conditions favoring the adoption of such a mixed MTS-MTO production strategy. Past studies ignore the influence of a one-to-many relation between semi-finished goods and products, and a guaranteed lead-time for MTO products, with uncertain product demand. The problem is modeled as a two-stage stochastic 0–1 integer, non-linear programming problem. In Stage 1, before demand realization, operations determine the product-wise mode of production and inventory level of semi-finished goods/MTS products, and marketing determine the guaranteed lead-time for MTO products. In Stage 2, product demand is realized, and it decreases linearly with lead-time and has a stochastic error component. The demand for MTS products is fulfilled from available inventory, and semi-finished goods are allocated to meet the demand of MTO products and build a stock of MTS products. The objective is to maximize the expected profit per-unit time. Sensitivity analysis of key problem parameters demonstrates that: (1) the integrated-firm can provide smaller lead-times under demand variability, (2) high holding cost of semi-finished goods, high lead-time sensitivity of demand, and high demand variability & low production rate promote mixed strategy over MTO strategy, and (3) high demand variability promotes substitution among semi-finished goods. A Hybrid Greedy and Non-linear Branch & Bound method (featuring problem-specific cuts and search & branching strategy) is proposed to solve real-life problems. This method provides a better solution and a smaller relative gap than commercial solver Simple Branch and Bound.
ISSN:	0360-8352 1879-0550
DOI:	10.1016/j.cie.2020.106603