The impact of controllable production rates on the performance of inventory systems: A systematic review of the literature

Glock, C. H.; Grosse, E. H.

doi:10.1016/j.ejor.2020.05.033

Cited by 42 publications

(14 citation statements)

References 139 publications

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“…It could be done by applying Collaborative Planning, Forecasting, and Replenishment (CPFR). It can improve supply chain management performance at various levels of the supply chain, including manufacturing [71], vendor-managed inventory [72], and supplier [73,74]. In addition, the CPFR ensures that the vocal companies and their supply chain partners have the same accurate information about demand.…”

Section: Managerial Implicationsmentioning

confidence: 99%

Optimization of Joint Economic Lot Size Model for Vendor‐Buyer with Exponential Quality Degradation and Transportation by Chimp Optimization Algorithm

2022

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Freight transportation plays a critical role in improving company performance in the modern manufacturing industry. To reduce costs, companies must take advantage of the use of large vehicles. It caused fewer deliveries, but inventory costs and degradation quality are high. One of the joint economic lot size (JELS) problems in supply chain is Integrated Single-Vendor Single-Buyer Inventory Problem (I-SVSB-IP). This study developed the I-SVSB-IP model that considers raw materials’ exponential quality degradation and transportation costs. The objective function of this research was to maximize the Joint Total Profit (JTP). Three decision variables used were inventory cycle time (T), raw material ordering frequency (m), and frequency of delivery of finished products to buyers (n). This study proposed a sophisticated Chimp Optimization Algorithm (ChOA) procedure to solve the I-SVSB-IP problem. A case study on the food industry in Indonesia was presented to optimize the I-SVSB-IP. The results showed that the ChOA procedure had produced an optimal solution compared to the state-of-the-art algorithm. This study also demonstrated a sensitivity analysis of decision and transportation variables to cost, revenue, and JTP. The results show that increasing transport frequency of ordering raw materials (m) and finished products to buyers (n) enhances the total cost and reduces joint total profit. In addition, increasing the rate of quality degradation of raw materials reduces JTP.

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Section: Managerial Implicationsmentioning

confidence: 99%

Optimization of Joint Economic Lot Size Model for Vendor‐Buyer with Exponential Quality Degradation and Transportation by Chimp Optimization Algorithm

2022

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“…According to Tranfield, Denyer and Smart (2003), SLR minimized the research bias through an extensive literature selection system and provided an audit evaluation trail towards the reviewer procedures, which is categorized as a scientific and transparent process. Hence, it can be said that the findings obtained from the SLR would be much easier to verify, interpret and follow through rather than traditional reviews (Glock & Grosse, 2021). Due to the benefits given by SLR, it will lead to the current literature review process a more accurate.…”

Section: The Need For Systematic Literature Review (Slr)mentioning

confidence: 99%

Company Strategies on Social Well-being during COVID-19 Pandemic: A systematic literature review

Rahim

Malek

Muhammad³

et al. 2022

E-BPJ

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In the competitive world of business, companies need to always be prepared in facing external threats that could put their sustainability in danger. The most recent crisis that had put businesses in a threat is the emergence of Covid-19 pandemic on December 2019. The purpose of the systematic review is to analyse the measures or strategies adopted by companies in order to cope with Covid-19 crisis. Based on the review conducted, several recommendations are highlighted to ensure in the future, company are more ready to face any crises beforehand. Keywords: Businesses; Strategies; Covid-19; Sustainability eISSN: 2398-4287 © 2022. The Authors. Published for AMER ABRA cE-Bs by e-International Publishing House, Ltd., UK. This is an open access article under the CC BYNC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Peer–review under responsibility of AMER (Association of Malaysian Environment-Behaviour Researchers), ABRA (Association of Behavioural Researchers on Asians/Africans/Arabians) and cE-Bs (Centre for Environment-Behaviour Studies), Faculty of Architecture, Planning & Surveying, Universiti Teknologi MARA, Malaysia. DOI: https://doi.org/10.21834/ebpj.v7i20.3348

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“…The purpose is to develop a workable production plan that fits the specifications and specifies release dates and quantities for all of the goods, including component parts. Finding a plausible strategy is insufficient for economic reasons (Glock and Grosse, 2021). An objective function can be used to evaluate production plans (e.g.…”

Section: Introductionmentioning

confidence: 99%

Unleashing an ML-based selection criteria for economic lot sizing in a smart batch-type production system

Kumar

Singh

Khope³

2022

TQM

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PurposeInventory models are quantitative ways of calculating low-cost operating systems. These models can be either deterministic or stochastic. A deterministic model hypothesizes variable quantities like demand and lead time, as certain. However, various types of research have revealed that the value of demand and lead time is still ambiguous and vary unanimously. The main purpose of this research piece is to reduce the uncertainties in such a dynamic environment of Industry 4.0.Design/methodology/approachThe current study tackles the multiperiod single-item inventory lot-size problem with varying demands. The three lot sizing policies – Lot for Lot, Silver–Meal heuristic and Wagner–Whitin algorithm – are reviewed and analyzed. The suggested machine learning (ML)–based technique implies the criteria, when and which of these inventory models (with varying demands and safety stock) are best fit (or suitable) for economical production.FindingsWhen demand surpasses a predicted value, variance in demand comes into the picture. So the current work considers these things and formulates the proper lot size, which can fix this dynamic situation. To deduce sufficient lot size, all three considered stochastic models are explored exclusively, as per respective protocols, and have been analyzed collectively through suitable regression analysis. Further, the ML-based Classification And Regression Tree (CART) algorithm is used strategically to predict which model would be economical (or have the least inventory cost) with continuously varying demand and other inventory attributes.Originality/valueThe ML-based CART algorithm has rarely been seen to provide logical assistance to inventory practitioners in making wise-decision, while selecting inventory control models in dynamic batch-type production systems.

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The impact of controllable production rates on the performance of inventory systems: A systematic review of the literature

Cited by 42 publications

References 139 publications

Optimization of Joint Economic Lot Size Model for Vendor‐Buyer with Exponential Quality Degradation and Transportation by Chimp Optimization Algorithm

Optimization of Joint Economic Lot Size Model for Vendor‐Buyer with Exponential Quality Degradation and Transportation by Chimp Optimization Algorithm

Company Strategies on Social Well-being during COVID-19 Pandemic: A systematic literature review

Unleashing an ML-based selection criteria for economic lot sizing in a smart batch-type production system

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