Title: Customers scheduling and clustering as vendor managed inventory enablers
Authors: Mariana Guersola; Maria Teresinha Steiner; Cassius Scarpin
Addresses: R. Imaculada Conceição, 1155, Escola Politécnica – Bloco 2 – 2º Andar, Prado Velho – Curitiba-PR, CEP: 80.215-901, Brazil ' R. Imaculada Conceição, 1155, Escola Politécnica – Bloco 2 – 2º Andar, Prado Velho – Curitiba-PR, CEP: 80.215-901, Brazil ' Programa de Pós-graduação em Engenharia de Produção, Universidade Federal do Paraná – Centro Politécnico, Setor de Tecnologia, Caixa Postal 19011, Jardim das Américas – CEP 81531-990, Curitiba – PR, Brazil
Abstract: The vendor managed inventory (VMI) implementation brings advantages to both vendors and customers, improving service levels and transportation efficiency. This paper aims to propose a two stages methodology to enable the VMI implementation without electronic data interchange. First, an algorithm is proposed to determine which customers to attend daily, respecting their needs and restrictions while seeking for economies of scale. Then an iterated local search metaheuristic, adapted to the capacitated p-median problem is proposed to divide the customers into the available trucks. The methodology was applied to a gas distribution case study. Results shown a 20.16% increase in the average quantity of gas delivered per customer, a drop over 90% in delivery delays and a reduction of 31.8% in clusters distances. These results demonstrate that the methodology improves the reliability of the distribution system, ensuring that the VMI implementation brings advantages to all parts involved.
Keywords: vendor managed inventory; VMI; electronic data interchange; EDI; capacitated p-median problem; iterated local search; ILS; transportation management; economies of scale; distances reduction; delivery system; liquefied petroleum gas; LPG; functional product.
DOI: 10.1504/IJLSM.2019.102063
International Journal of Logistics Systems and Management, 2019 Vol.34 No.1, pp.56 - 74
Accepted: 22 Jan 2018
Published online: 05 Sep 2019 *