Lost sales reduction and quality improvement with variable lead time and fuzzy costs in an imperfect production system

Abstract

This article investigates the effects of lost sales reduction and quality improvement in an imperfect production process under imprecise environment with simultaneously optimizing reorder point, order quantity, and lead time. This study assumes that the demand during lead time follows a mixture of normal distributions and the cost components are imprecise and vague. Under these assumptions, the aim is to study the lost sales reduction and the quality improvement in an uncertainty environment. The objective function in fuzzy sense is defuzzified using Modified Graded Mean Integration Representation Method (MGMIRM). For the defuzzified objective function, theoretical results are developed to establish optimal policies. Finally, some numerical examples and sensitivity analysis are provided to examine the effects of non-stochastic uncertainty.

Multiple Attribute Decision-Making Methods Based on Normal Intuitionistic Fuzzy Interaction Aggregation Operators

“…The significant characteristics of the proposed method are that: (1) it is easier to describe the uncertain information than the existing fuzzy sets and stochastic variables; (2) it used the interaction operations in part of IFSs which could overcome the existing weaknesses in operational rules of NIFNs; (3) it adopted PA operator which could relieve the influence of unreasonable data given by biased decision makers; and (4) it made the decision-making results more flexible and reliable because it was with generalized parameter that could be regarded as the risk attitude value of decision makers. In the future, we will study the applications of the proposed operators and method for the MADM problems with normal distribution stochastic information [37,38], especially for supply chain managements [39] and inventory models [40,41], or study the fuzzy graphs or trees based on NIFNs [42][43][44][45].…”

Coordinating Supply-Chain Management under Stochastic Fuzzy Environment and Lead-Time Reduction

“…Furthermore, Jha and Shanker [25] extended it to single-vendor multi-buyer model. Soni et al [26] studied an imperfect production-inventory model with fuzzy costs, controllable lead time, and investment for lost sales reduction and quality improvement.…”

Minimum Quantity Lubrication and Carbon Footprint: A Step towards Sustainability

“…Inderfurth et al [42] proposed an inventory model to ensure that the defective items also produced commonly in same production facility. Various researchers worked on imperfect production system to reflect the real scenario of industry (See: [43][44][45][46]). From the solution methodology perspective, Minjung developed a mixed integer linear programming (MILP) model to optimize the remanufacturing plan to justify justify the economic and environmental benefits of a product [47].…”