In light of recently increased e-commerce, also a result of the COVID-19 pandemic, this study examines how additive manufacturing (AM) can contribute to e-commerce supply chain network resilience, ...profitability and competitiveness. With the recent competitive supply chain challenges, companies aim to decrease cost performance metrics and increase responsiveness. In this work, we aim to establish utilisation policies for AM in a supply chain network so that companies can simultaneously improve their total network cost and response time performance metrics. We propose three different utilisation policies, i.e. reactive, proactive – both with 3D printing support – and a policy excluding AM usage in the system. A simulation optimisation process for 136 experiments under various input design factors for an (s, S) inventory control policy is carried out. We also completed a statistical analysis to identify significant factors (i.e. AM, holding cost, lead time, response time, demand amount, etc.) affecting the performance of the studied retailer supply chain. Results show that utilising AM in such a network can prove beneficial, and where the reactive policy contributes significantly to the network performance metrics. Practically, this work has important managerial implications in defining the most appropriate policies to achieve optimisation of supply network operations and resilience with the aid of AM, especially in times of turbulence and uncertainty.
Aiming at the low quality of the solution obtained with the traditional marginal analysis algorithm for solving multi‐level inventory optimisation problem of repairable spare parts, a hybrid ...algorithm integrating particle swarm optimisation, marginal analysis algorithm‐METRIC model and tabu search is proposed. In the early stage of the hybrid algorithm, particle swarm optimisation is used to explore the global solution space and in the later stage, tabu search is used to local search, and the marginal analysis algorithm is used to constructing neighbourhood. The experimental results show that the proposed algorithm can solve the problem of spare parts multi‐level inventory optimisation effectively and efficiently.
Even though base-stock policies are per se straightforward, determining them in complex, stochastic multi-echelon supply chains is often cumbersome or even analytically impossible. Therefore, a wide ...range of heuristics has been proposed for this purpose. This is the first study considering the problem as a multi-armed bandit problem. In this context, we investigate two algorithms: first, we propose an approach that is based on upper confidence bounds and priority queues. This so-called PQ-UCB algorithm allows us to drastically reduce the runtime of upper confidence bound allocation strategies in problems with large action spaces. Subsequently, we apply the parameter-free sequential halving (SH) algorithm. We investigate various scenarios to compare the performance of both algorithms with the performance of a genetic algorithm and a simulated annealing algorithm taken from the literature. PQ-UCB as well as SH outperform both benchmark metaheuristics and require substantially less effort related to parameter tuning (or even no effort in the case of SH). As multi-armed bandits are not common in inventory optimisation so far, we aim to emphasise their strengths and hope to promote their dissemination also in other domains of supply chain management.
Demand uncertainties and delivery delays are the fundamental causes of poor inventory control, especially in a dual-channel supply chain. Considering the impact of stochastic demand on the ...dual-channel inventory. this study explores the dynamic interactions of online-offline purchase-sale-stock systems under the decentralised, centralised, and cross-replenishment inventory controls. Hence, this study constructs a dynamic inventory model with delivery delays, based on the feedback and proportional-integral-derivative control, to optimise the influences between the replenishment cycles and online-offline channels' interactions. The results show that, when the channels follow different sales strategies and the warehouses are proximally located, the cross-replenishment inventory strategy reduces the residual inventory. When the channels follow the same sales strategies, the centralised inventory control reduces the residual inventory. These findings demonstrate that the dynamic interactive inventory model can contribute towards optimising inventory operations. This study presents substantial insights for improving the overall performances of the dual-channel supply chain from the perspectives of dynamic and interactive inventory control, warehouse and retail network optimisation, and resource allocation.
Segmenting large supply chains into lean and agile segments has become a powerful strategy allowing companies to manage different market demands effectively. A current stream of research into supply ...chain segmentation proposes demand volume and variability as the key segmentation criteria. This literature adequately justifies these criteria and analyses the benefits of segmentation. However, current work fails to provide approaches for allocating products to segments which go beyond simple rules of thumb, such as 80-20 Pareto rules. We propose a joint network and safety stock optimisation model which optimally allocates Stock Keeping Units (SKUs) to segments. We use this model, populated both with synthetic data and data from a real case study and demonstrate that this approach significantly improves cost when compared to using simple rules of thumb alone.
Nowadays, due to the increasing complexity of business environment, especially demand uncertainty, supply chain managers need to establish more-effective sourcing and distribution strategies to ...ensure high customer service and low stock costs. To overcome this challenge multi-echelon network structures and alternative distribution strategies such as lateral transshipments and multiple sourcing should be considered in inventory optimisation models. In this article, we propose a scenario-based modelling approach to solve a two-stage multi-echelon inventory optimisation problem with a non-stationary demand. The model is based on a distribution requirements planning (DRP) approach and minimises the expected total cost that is composed of the fixed allocation, inventory holding, procurement, transportation, and back-ordering costs. Alternative inventory optimisation models, including the lateral transshipment strategy and multiple sourcing, are thus built, and the corresponding stochastic programmes are solved using the sample average approximation method. Through a numerical investigation conducted with several generated instances and an empirical investigation based on the case of a major French retailer's distribution network, we show the substantial benefit of lateral transshipments and multiple sourcing in reducing the expected total costs of the distribution network.
•Efficient compression of huge corpus-based TTS unit selection acoustic space.•A novel look-up of acoustic units' concatenation costs as a seq-2-seq problem.•Efficient compression of concatenation ...costs by using a LSTM model.•Reduction of memory footprint by over 90%, the look-up time reduced by over 70%.
Large acoustic inventories must be used to produce speech close to natural quality. However, the concatenation cost space grows exponentially with the number of acoustic units in the acoustic inventory, increasing the latency of the unit selection algorithm, making algorithms unusable in real-time end-to-end systems. Even when data compression techniques are introduced, the model size is still high, representing a challenge for end-to-end systems. Thus, in this paper, we propose representing the concatenation cost space using LSTM (Long Short-Term Memory). The results show a 90% reduction in the size of the data space compared to all our previous techniques, and by an over 70% decrease in the look-up time. The proposed LSTM-based compression increases the responsiveness of the corpus-based text-to-speech systems significantly while keeping the overall speech quality at the same level.
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More recent research shows the significant impact of accurate demand forecasting on the operation of supply chain system and thus on the performance of the company. Inventories in the production ...process could represent waste, which results in higher storage costs and consequently a higher product price, which in turn reduces company's competitiveness on the market. Nevertheless, a company must implement a lean production process and consequently carefully control storage and inventory costs. The introduction of a lean production process is closely linked to the risk of stock-outs, and knowledge of this risk in relation to customer habits is therefore a useful piece of information for the line manager's decision-making. This paper will present a mathematical model that relates customer demand for a product to the inventory level in the warehouse or between the work operations of the production process and the risk of potential penalties that arises with the introduction of a lean production process. With this model we can simulate, how to improve the production processes with still acceptable risk, with the goal of achieving a balance between stocks and the leanness of the production process. The paper demonstrates the use of a mathematical model on a concrete example from practice for risk simulation when choosing different production scenarios resulting from changed customer behaviour.
AbstractThis paper aims to assess the effect of inventory control systems on performance of mining firms in Zimbabwe. A systematic literature review was used to review current and relevant scholarly ...work. The paper used a quantitative survey approach where a survey questionnaire was utilized to collect quantitative primary data from 203 respondents in mining companies. IBM SPSS AMOS version 22 statistical tool was used to conduct Structural Equation Modelling and Confirmatory Factor Analysis. SEM was used to test the formulated hypotheses and CFA was used to determine convergent and discriminant validities of measurement models. The results of this research reveal a positive direct and positive indirect effect of inventory control systems on performance of mining firms in Zimbabwe. Therefore, the research concludes that inventory control systems are used to optimize inventory levels to avoid high inventory ordering and holding costs and stockouts of raw materials and spare parts in mining firms. Thus, mining firms are recommended to use inventory control systems mentioned in this paper to optimize inventories of raw materials and spare parts to improve their performances. This paper also suggests the implementation of modern computerised inventory control systems for effective inventory control in mining firms in Zimbabwe.
Background Order allocation planning and inventory management are two important problems in manufacturing industries that must be solved optimally to gain maximal profit. Commonly, there are several ...unknown parameters in those problems such as future price, future demand, etc., and this means decision-making support that can handle this uncertainty is needed to calculate an optimal decision.Objectives This study aimed to propose a newly developed joint decision-making support to solve order allocation planning and inventory optimisation of raw materials in a production system comprising multiple suppliers, products and review times with fuzzy parameters.Method The model was formulated as a fuzzy expectation-based quadratic programming with the uncertain parameters approached as fuzzy numbers. This was used to handle the fuzzy parameters involved in the problem. A classical optimisation algorithm, the generalised reduced gradient combined with branch-and-bound embedded in LINGO 18.0 was applied to calculate the optimal decision. Numerical experiments were conducted using some randomly generated data with four suppliers, four raw materials and six review times.Results Results provided the optimal decision for the given problem, that is, the number of raw materials to be ordered from each supplier at each review time, as well as the corresponding number to be stored in the warehouse.Conclusion The proposed model successfully solved the given problems and thus can be used by decision-makers to solve their order allocation planning and inventory problems.
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