An Inventory Model under Space Constraint in Neutrosophic Environment: A Neutrosophic Geometric Programming Approach

In this paper, an inventory model is developed without shortages where the production cost is inversely related to the set up cost and production quantity. In addition, the holding cost is considered time dependent. Here impreciseness is introduced in the storage area. The objective and constraint functions are defined by the truth (membership) degree, indeterminacy (hesitation) degree and falsity (non-membership) degree. Likewise, a non-linear programming problem with a constraint is also considered. Then these are solved by Neutrosophic Geometric Programming Technique for linear membership, hesitation and non-membership functions. Also the solution procedure for Neutrosophic Non-linear Programming Problem is proposed by using additive operator and Geometric Programming method. Numerical examples are presented to illustrate the models using the proposed procedure and the results are compared with the results obtained by other optimization techniques

Optimization of EOQ Model with Limited Storage Capacity by Neutrosophic Geometric Programming

In this article, we present deterministic single objective economic order quantity model with limited storage capacity in neutrosophic environment. We consider variable limit production cost and time dependent holding cost into account. Here we minimize total average cost of proposed model by applying neutrosophic geometric programming, which is obtained by extending existing fuzzy and intuitionistic fuzzy geometric programming for solving resultant non-linear optimization model. Next we consider numerical application to show that optimal solution obtained by neutrosophic geometric programming is more desirable than that of crisp, fuzzy and intuitionistic fuzzy geometric programming. Also we perform sensitivity analysis of parameters and present key managerial insights

Perspective Chapter: Downscaling of Satellite Soil Moisture Estimates

Soil moisture is a key parameter in the hydrological cycle and plays a critical role in global climate. The capacity to forecast drought and floods, manage water resources, and make field-scale decisions depends on accurate and thorough information on soil moisture. In addition to the instrument-based field observation approaches, dynamic mapping of soil moisture has been made possible by satellite remote sensing technologies. Estimates of soil moisture at a global and regional scale from optical and thermal remote sensing have been explored, and considerable advancements have been made. However, these global soil moisture products have coarse spatial resolutions and are typically unsuitable for field-level hydrological and agricultural applications. In this regard, this chapter presents a comprehensive review of the latest downscaling methods to improve the coarse-spatial and temporal resolution of soil moisture products. The main approaches discussed in the chapter include active passive fusion, optical/thermal based, topography based, and data assimilation methods. The physical background, current status, advantages and limitations associated with each downscaling approach has been thoroughly examined. Each of these optical/thermal, microwave-based methods for soil moisture estimation involves intricate derivation at different spatiotemporal scales, which can be combined using recent advances in machine learning

Implementation of an early rule-out pathway for myocardial infarction using a high-sensitivity cardiac troponin T assay.

OBJECTIVES: Patients with suspected acute coronary syndrome and high-sensitivity cardiac troponin (hs-cTn) concentrations below the limit of detection at presentation are low risk. We aim to determine whether implementing this approach facilitates the safe early discharge of patients. METHODS: In a prospective single-centre cohort study, consecutive patients with suspected acute coronary syndrome were included before (standard care) and after (intervention) implementation of an early rule-out pathway. During standard care, myocardial infarction was ruled out if hs-cTnT concentrations were <99th centile (14 ng/L) at presentation and at 6-12 hours after symptom onset. In the intervention, patients were ruled out if hs-cTnT concentrations were <5 ng/L at presentation and symptoms present for ≥3 hours or were ≥5 ng/L and unchanged within the reference range at 3 hours. We compared duration of stay (efficacy) and all-cause death at 1 year (safety) before and after implementation. RESULTS: We included 10 315 consecutive patients (64±16 years, 46% women) with 6642 (64%) and 3673 (36%) in the standard care and intervention groups, respectively. Duration of stay was reduced from 534 (IQR, 220-2279) to 390 (IQR, 218-1910) min (p<0.001) after implementation. At 1 year, all-cause death occurred in 10.9% (721 of 6642) and 10.4% (381 of 3673) of patients in the standard care group (referent) and intervention group, respectively (adjusted OR 1.02, 95% CI 0.88 to 1.18). CONCLUSION: In patients with suspected acute coronary syndrome, implementing an early rule-out pathway using hs-cTnT concentrations <5 ng/L at presentation reduced the duration of stay in hospital without compromising safety

Optimization of generalized order-level inventory system under fully permissible delay in payment

This article presents one generalized order-level inventory system with fully permissible delay in payment in various trade-credit intervals. Review of existing literature finds few EOQ models under simultaneous considerations of time-dependent generalized demand rate, time-dependent generalized rate of deterioration and time-dependent generalized backordering under fully permissible delay in payment. In those existing studies, the optimal inventory depletion time is independent of demand over the entire cycle. Here, present article frames one generalized order-level inventory system with fully permissible delay in payment across various trade-credit intervals. This finds that when the trade-credit period is longer than the inventory depletion time to settle the account, the optimal inventory depletion time is dependent of demand. Under this ambiance, one particular case having time-dependent ramp type demand rate, two variables time-dependent Weibull distribution rate of deterioration and time-dependent backordering rate with fully permissible delay in payment, finds that the optimal inventory depletion time varies inversely over demand in that period. Moreover, the proposed model shrinks to obtain many well-established EOQ models as the special cases to it. Next, a general algorithm determines the various optimal solutions corresponding to seven cases. The managerial insights extracted from sensitivity analysis of parameters include the suggestion to halt the promotional activities so as to foreshorten the demand in shortage period. Also, this analysis attests that the longer waiting period of retailers should be counterbalanced with various promotional activities and anticipated benefits

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