Optimisation-in-the-loop simulation of multi products single vendor-multi buyers supply chain systems with reactive lateral transhipment

Considering that batik is one of the most popular products in Indonesia, it is important to analyse the supply chain system for batik products. In reality, the supply chain system for batik products enables orders between buyers to receive products more rapidly, allowing them to anticipate stock outs and obtain lower ordering costs than when ordering from vendors. It is referred to as reactive lateral transshipment. This paper discusses the development of a simulation-based stochastic optimisation model for a batik product supply chain system with multiproducts and single vendor-multi buyers. The utilised solution searching algorithm is a modified Genetic Algorithms (GA) executed in-loop with the developed simulation-based stochastic model. The results demonstrate that the proposed modified GA is able to provide a global optimum solution, allowing the proposed simulation-based stochastic model to reduce the joint total cost (JTC) of the investigated supply chain system by up to 19% when compared to the local optimisation model in each supply chain party

Diseño de un aplicativo que determine las políticas de inventarios en una empresa de productos lácteos

El trabajo aborda el problema de distribución interno en una empresa de productos lácteos cuyo sistema opera bajo varios centros de distribución nacional y regional. El problema se puede clasificar dentro de la categoría de IRP con transshipment, donde se pretende determinar la cantidad y el momento de atención para cada uno de los centros de distribución de tal forma que se minimice el costo total logístico. El caso presentado tiene en cuenta una variedad productos perecederos determinada, leadtimes diferentes y un horizonte de planeación establecido. Debido a las características de los productos y del sistema, se encontró que este no ha sido abordado dentro de la literatura, por lo que en este artículo se plantea un acercamiento a la solución del mismo, buscando la reducción de costos y la coordinación del sistema de distribución. Para la resolución del problema se realizó un modelo matemático que contiene todas las restricciones pertinentes, entre las cuales se destaca la del tiempo de caducidad de ciertos productos, lo que implica que las decisiones dependen no solo del costo sino también del tiempo. Adicionalmente, y debido a la limitación del software de optimización para resolver problemas con instancias grandes, se adaptó la metaheurística ALNS para dar solución al problema. Los resultados presentados muestran el comportamiento de la heurística en 20 instancias diferentes modificando el tipo de transshipment, la cantidad de nodos y de productos. Se realizó una comparación con una cota inferior del costo total aproximado del modelo matemático con las variables enteras relajadas, obteniendo resultados satisfactorios por parte de la metaheurística.The paper addresses the problem of internal distribution in a dairy company whose system operates under several national and regional distribution centers. The problem can be classified within the category of IRP with transshipment, where it is intended to determine the quantity and timing of care for each of the distribution centers in such a way as to minimize the total logistic cost. The case presented takes into account a variety of perishables products, different leadtimes and an established planning horizon. Due to the characteristics of the products and the system, it was found that this has not been approached within the literature, so in this article it is proposed an approach to the solution of the same, looking for the reduction of costs and the coordination of the system of distribution. In order to solve the problem, a mathematical model was developed which contains all the relevant restrictions, among which the expiration time of certain products stands out, which implies that decisions depend not only on cost but also on time. In addition, due to the limitation of the optimization software to solve problems with large instances, the ALNS metaheuristic was adapted to solve the problem. The results presented show the behavior of the heuristic in 20 different instances modifying the type of transshipment, the number of nodes and products. A comparison was made with a lower bound of the approximate total cost of the mathematical model with the whole relaxed variables, obtaining satisfactory results on the part of the metaheuristic.Ingeniero (a) IndustrialPregrad

Inventory model for a multi-echelon system with unidirectional lateral transshipment

Inventory management constitutes a fundamental decision-making problem, especially in systems which must guarantee high availability levels. In complex multi-echelon networks, in case of shortage at a location, resupplying from a near location on the same echelon rather than from the original supplier at the upper echelon, would be a potential faster and then more profitable policy. A wide interest in literature shows the importance of this policy, i.e. the lateral transhipment (LTR), as a means to reduce the inventory costs. This paper deals with unidirectional LTR, which often represent a reasonable policy in scenarios where backorders have different effects on the system. Based on METRIC, this paper defines a system-approach model for determining the stock levels of repairable items in a complex network, by a genetic algorithm optimization process. The model considers non-zero maintenance time for each item and different skills of maintenance centres, in a multi-echelon single-indenture system, with unidirectional LTR allowed. The expert system developed in the paper assists the decision maker to define the inventory levels for the maintenance sites across the system, taking advantage of the LTR to reduce costs and enhance availability. A case study of a European airline shows the relevance of the developed expert system, also considering its reproducibility to face different industrial contexts

Transshipment in supply chain networks with perishable items

Supply chain management is an efficient approach to managing the flow of information, goods, and services in fulfillment of customer demand. The implementation of supply chain management significantly affects the cost, benefit level, and quality. Over the past decades, multiple strategies for effective supply chain management have been developed in both academia and industry. One such strategy is named lateral transshipment which allows movement of stock between locations at the same echelon level or even across different levels. Although transshipment has been considered in the literature for a long time, there has been limited studies of transshipment for perishable items, most likely because of the complex structure of perishable inventories. The analysis of perishable-inventory systems has been considered in numerous articles because of its potential application in sectors such as chemicals, food, photography, pharmaceuticals, and blood bank management. Blood services in Australia rely on voluntary, non-remunerated donors to satisfy the demand for blood. Blood services confront ongoing challenges in providing an adequate supply of blood and blood products. One of the powerful tools that could improve the efficiency of the blood supply chain is lateral transshipment. This thesis presents three models that have application in the transshipment of perishable items such as blood. The first model (presented in Chapter 2) outlines the development of a new transshipment policy for perishable items, to enhance supply chain performance. A Poissondistributed customer demand is assumed and the effect of reactive transshipment on expected costs are evaluated. A heuristic solution is developed, using partial differential equations to compute performance measures and cost function. The performance of this model is evaluated through a numerical study. The results indicate that this transshipment policy is effective under lost-sale and backordering scenarios. In addition, the performance of the suggested transshipment policy is compared with the current transshipment policy that is practiced in some Australian hospitals. The results suggest that by setting the optimal threshold, a significant cost saving could be obtained with the same average issuing age of the current policy. The second model (presented in Chapter 3) considers a finite-horizon multi-period inventory system with one main hospital connected to several smaller hospitals. The hospitals face random demand and small hospitals are allowed to transship to the big hospital to mitigate their wastage. The problem is formulated as an infinite-horizon dynamic programming model. The objective of this model is to determine an optimal ordering and transshipment policy that minimizes the total expected cost. An approximate dynamic programming (ADP) model is used to approximate the value function with a linear combination of basis functions, using column generation to cope with the course of dimensionality. The numerical results suggest that considerable cost saving can be achieved by using an ADP model. The third model (presented in Chapter 4) proposes a proactive transshipment policy for a network of hospitals with uncertain demand. At the beginning of each review period, each hospital makes decisions on the quantity to order from a central blood bank and to transship to other hospitals. The problem is formulated as a two-stage stochastic programming model where the Quasi-Monte Carlo (QMC) sampling approach is used to generate scenarios and the optimal number of scenarios is determined by conducting stability tests. The performance of the developed model is evaluated through numerical experiences. The numerical results indicate significant potential cost savings in comparison with the current policy in use and the no-transshipment policy