Economic disposal quantity of leftovers kept in storage : a Monte Carlo simulation method

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Data

2019

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De Gruyter Open Access

Resumo

This article describes how to reach an item's threshold, or in other words, the limit time for it to be retrieved from stock and sold for a different use, as well as the remaining foreseen period for this situation to occur. Once a minimum length, or weight, is reached, left quantities are more difficult to sell, as demand often exceeds the remaining parts or leftovers. The number of unfulfilled orders increases, as time goes by, until it becomes further cost effective to dispose the leftover and sell it for a lower price and alternative use. A Monte Carlo simulation model was built in order to consider the randomness of future transactions and quantifying consequences providing this way a simple and effective decision-making framework.
This article describes how to reach an item’s threshold, or in other words, the limit time for it to be re 5 trieved from stock and sold for a different use, as well as the remaining foreseen period for this situation to occur. Once a minimum length, or weight, is reached, left quan tities are more difficult to sell, as demand often exceeds the remaining parts or leftovers. The number of unfulfilled 10 orders increases, as time goes by, until it becomes further cost effective to dispose the leftover and sell it for a lower price and alternative use. A Monte Carlo simulation model was built in order to consider the randomness of future transactions and quantifying consequences providing this 15 way a simple and effective decision-making. KEYWORDS: Decision-making ; Economical Optimization ; Monte-Carlo Simulation ; Stochastic Process

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Palavras-chave

GESTÃO, TOMADA DE DECISÃO, OTIMIZAÇÃO, PROCESSOS ESTOCÁSTICOS, MÉTODO MONTE CARLO, ECONOMIA, MANAGEMENT, DECISION MAKING, OPTIMIZATION, STOCHASTIC PROCESSES, MONTE CARLO METHOD, ECONOMY, STOCK MANAGEMENT

Citação

Assis, R, Marques, P C, Santos, J O & Vidal, R 2019, 'Economic disposal quantity of leftovers kept in storage : a Monte Carlo simulation method', Open Engineering, vol. 9, no. 1, pp. 522–529. https://doi.org/10.1515/eng-2019-0062

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