929 research outputs found

    Integrated optimisation for production capacity, raw material ordering and production planning under time and quantity uncertainties based on two case studies

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    Abstract This paper develops a supply chain (SC) model by integrating raw material ordering and production planning, and production capacity decisions based upon two case studies in manufacturing firms. Multiple types of uncertainties are considered; including: time-related uncertainty (that exists in lead-time and delay) and quantity-related uncertainty (that exists in information and material flows). The SC model consists of several sub-models, which are first formulated mathematically. Simulation (simulation-based stochastic approximation) and genetic algorithm tools are then developed to evaluate several non-parameterised strategies and optimise two parameterised strategies. Experiments are conducted to contrast these strategies, quantify their relative performance, and illustrate the value of information and the impact of uncertainties. These case studies provide useful insights into understanding to what degree the integrated planning model including production capacity decisions could benefit economically in different scenarios, which types of data should be shared, and how these data could be utilised to achieve a better SC system. This study provides insights for small and middle-sized firm management to make better decisions regarding production capacity issues with respect to external uncertainty and/or disruptions; e.g. trade wars and pandemics.</jats:p

    Vendor Managed Inventory: why you need to talk to your supplier

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    Purpose The purpose of this paper is to investigate the concept of Vendor Managed Inventory (VMI) from an inter-organisational perspective. Extant literature on VMI tends to investigate the concept from a focal perspective, even though VMI has originally been born as a collaborative arrangement. Design/methodology/approach The paper is based on a literature review and an empirical study. It provides a comprehensive literature review on VMI and an illustrative case study of a supplier and a buyer jointly implementing VMI. Findings The findings of this paper are twofold. First, a literature review uncovers that contemporary research has delimited the analysis of VMI to a focal company perspective as current VMI cost models tend not to capture the picture of the complete supply chain. Second, it demonstrates through an illustrative case study that adoption of an inter-organisational approach to VMI is vital if companies are to optimize their buyer-supplier relationships. Research limitations/implications Future research should test the implications proposed in the empirical section, as this piece of research can be seen as exploratory case study research with the aim of analytical generalizations. Practical implications The inter-organisational VMI cost perspective in supply chains should be emphasized in purchasing departments since such a perspective significantly raises the awareness of the costs incurred in a supply chain. Originality/value Existing research has not explicitly focused on inter-organisational costs incurred by companies implementing VMI. This study seeks to bridge this research gapPeer Reviewe

    Vendor Managed Inventory: why you need to talk to your supplier

    Get PDF
    Purpose The purpose of this paper is to investigate the concept of Vendor Managed Inventory (VMI) from an inter-organisational perspective. Extant literature on VMI tends to investigate the concept from a focal perspective, even though VMI has originally been born as a collaborative arrangement. Design/methodology/approach The paper is based on a literature review and an empirical study. It provides a comprehensive literature review on VMI and an illustrative case study of a supplier and a buyer jointly implementing VMI. Findings The findings of this paper are twofold. First, a literature review uncovers that contemporary research has delimited the analysis of VMI to a focal company perspective as current VMI cost models tend not to capture the picture of the complete supply chain. Second, it demonstrates through an illustrative case study that adoption of an inter-organisational approach to VMI is vital if companies are to optimize their buyer-supplier relationships. Research limitations/implications Future research should test the implications proposed in the empirical section, as this piece of research can be seen as exploratory case study research with the aim of analytical generalizations. Practical implications The inter-organisational VMI cost perspective in supply chains should be emphasized in purchasing departments since such a perspective significantly raises the awareness of the costs incurred in a supply chain. Originality/value Existing research has not explicitly focused on inter-organisational costs incurred by companies implementing VMI. This study seeks to bridge this research gapPeer Reviewe

    The extension and exploitation of the inventory and order based production control system archetype from 1982 to 2015

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    In 1994, through classic control theory, John, Naim and Towill developed the ‘Automatic Pipeline, Inventory and Order-based Production Control System’ (APIOBPCS) which extended the original IOBPCS archetype developed by Towill in 1982 ─ well-recognised as a base framework for a production planning and control system. Due to the prevalence of the two original models in the last three decades in the academic and industrial communities, this paper aims to systematically review how the IOBPCS archetypes have been adopted, exploited and adapted to study the dynamics of individual production planning and control systems and whole supply chains. Using various databases such as Scopus, Web of Science, Google Scholar (111 papers), we found that the IOBPCS archetypes have been studied regarding the a) modification of four inherent policies related to forecasting, inventory, lead-time and pipeline to create a ‘family’ of models, b) adoption of the IOBPCS ‘family’ to reduce supply chain dynamics, and in particular bullwhip, c) extension of the IOBPCS family to represent different supply chain scenarios such as order-book based production control and closed-loop processes. Simulation is the most popular method adopted by researchers and the number of works based on discrete time based methods is greater than those utilising continuous time approaches. Most studies are conceptual with limited practical applications described. Future research needs to focus on cost, flexibility and sustainability in the context of supply chain dynamics and, although there are a few existing studies, more analytical approaches are required to gain robust insights into the influence of nonlinear elements on supply chain behaviour. Also, empirical exploitation of the existing models is recommended

    Modeling and solving the multi-period inventory routing problem with constant demand rates

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    The inventory routing problem (IRP) is one of the challenging optimization problems in supply chain logistics. It combines inventory control and vehicle routing optimization. The main purpose of the IRP is to determine optimal delivery times and quantities to be delivered to customers, as well as optimal vehicle routes to distribute these quantities. The IRP is an underlying logistical optimization problem for supply chains implementing vendor-managed inventory (VMI) policies, in which the supplier takes responsibility for the management of the customers' inventory. In this paper, we consider a multi-period inventory routing problem assuming constant demand rates (MP-CIRP). The proposed model is formulated as a linear mixed-integer program and solved with a Lagrangian relaxation method. The solution obtained by the Lagrangian relaxation method is then used to generate a close to optimal feasible solution of the MP-CIRP by solving a series of assignment problems. The numerical experiments carried out so far show that the proposed Lagrangian relaxation approach nds quite good solutions for the MP-CIRP and in reasonable computation times

    Decision support system for vendor managed inventory supply chain:a case study

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    Vendor-managed inventory (VMI) is a widely used collaborative inventory management policy in which manufacturers manages the inventory of retailers and takes responsibility for making decisions related to the timing and extent of inventory replenishment. VMI partnerships help organisations to reduce demand variability, inventory holding and distribution costs. This study provides empirical evidence that significant economic benefits can be achieved with the use of a genetic algorithm (GA)-based decision support system (DSS) in a VMI supply chain. A two-stage serial supply chain in which retailers and their supplier are operating VMI in an uncertain demand environment is studied. Performance was measured in terms of cost, profit, stockouts and service levels. The results generated from GA-based model were compared to traditional alternatives. The study found that the GA-based approach outperformed traditional methods and its use can be economically justified in small- and medium-sized enterprises (SMEs)
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