An integrated producer–buyer relationship in the environment of EMQ and JIT production systems

The philosophy of this paper is to build up a strong bond between a producer and a buyer. In this respect, an integrated producer–buyer inventory model with constant demand and small lot size is framed in two different production environments: an EMQ (economic manufacturing quantity)-based production environment and a JIT (just-in-time)-based production environment. Imperfect production with rework is considered for the producer while shortage and backlogging are introduced for the buyer. The joint total cost of the producer and buyer is minimised to determine the optimum rate of production and optimum shortage period for both cases. A comparative study is performed between these two cases using the numerical results in order to make a decision concerning the choice of a more convenient production system for small lot sizes. Sensitivity analyses are carried out together for both cases.     

Inventory lot-sizing with supplier selection under non-stationary stochastic demand

Inventory lot-sizing and supplier selection problem has been studied in the literature considering mainly time-varying deterministic demand. However, in real life, most of the products exhibit non-stationary stochastic demand. In this context, we propose an integer linear programming model for inventory lot-sizing and supplier selection problem under non-stationary stochastic demand with all-units quantity discounts and fill rate constraints. Through detailed analysis of experimental results, we show the impacts of fill rate requirements and demand coefficient of variation on costs, inventory levels and order allocations.     

Optimisation of multi-stage JIT production-pricing decision: centralised and decentralised models and algorithms

This research studies the optimal decision for product pricing, production lot sizing in a multi-stage serial just-in-time production system with kanban-controlled policy. A decentralised decision model and a centralised decision model of this problem are formulated as a mixed-integer nonlinear programming problem. In order to solve the models, three algorithms are developed. The first one is an approximate procedure which solves the decentralised decision model; the second one is a proximate optimal procedure using two-phase search technique that solves the centralised decision model, and the third one is an approximate method using meta-heuristic technique which is used for both decentralised and centralised models. Numerical example shows that centralised decision can obtain higher economic benefit with lower cost and higher revenue and profit. Meanwhile, when demand is more price sensitive, centralised decision can achieve significant profit enhancement. Computational results attribute to different characteristics of the problem and solution superiority.     

存货控制与经营效益研究

针对企业存货进行财务管理现状的分析,认为运用经济批量法对企业的存货进行订货控制,可以降低企业存货的订货成本和储存成本,从而提高经营效益.在资产项目财务管理中,作者引入了现代库存管理理念.     

Inventory control of an item with a probabilistic replenishment lead time and a known supplier shutdown period

In this paper, we address an important practical situation, namely where the usual replenishment lead time (when the supplier's production facility is operating) is a random variable and the supplier shuts down for an interval of known duration (for maintenance, vacation, etc.) each year. The demand rate is constant and any demand when out of stock is assumed to be lost. Under such circumstances we develop a heuristic procedure to decide when to initiate replenishment as well as the associated order-up-to-levels. Through the use of simulation (which accurately estimates the average costs per unit time), the heuristic is shown to perform excellently in a selection of small size problems when one can find the optimal solution. For a large number of problems of more realistic size, the use of simulation reveals that the heuristic achieves substantial cost savings when compared with a simpler, baseline approach. The heuristic itself does not require the use of simulation. The sensitivity of total expected costs to various parameters (such as the length of the shutdown interval and characteristics of the lead time distribution) is discussed.     

The supplier–buyer integrated production-inventory model with random yield

This paper revisits the traditional supplier–buyer integrated production-inventory model which deals with the problem of a manufacturer (supplier) supplying a product to a retailer (buyer) serving the consumer market with constant stationary demand. The product is manufactured in batches at a finite rate. The supplier's production batch is depleted by the buyer's replenishment orders at periodic intervals. The buyer's inventory is then consumed by the market demand at a fixed rate. The problem is the simultaneous computation of the manufacturer's production lot-size and the buyer's replenishment order quantity, i.e. the integrated production-inventory policy parameters. The key characteristic considered in this paper is that the manufacturing process is imperfect, and, hence, there are defective items in each production lot. As a result, each replenishment order shipped to the buyer includes defective products and the non-defective percentage in each such shipment is random. Considering the case where the supplier replenishes the buyer via equal-sized shipments, we develop an analytical expression of the total expected cost for the supplier–buyer system under consideration, with and without a considerable inspection time. We first examine the case where the inspection time is negligible, and then we present a generalisation to consider the inspection time explicitly. Our goal is to model the impact of random yield on the system performance. Our findings are useful for computing the integrated production-inventory policy parameters while considering the supply uncertainty due to an imperfect manufacturing process. Through numerical examples, we quantify the impact of supply with random yield on the system performance and illustrate its relationship with the demand and production rate.     

基于极大熵的单周期产品库存模型

研究具有自由需求分布的单周期问题。建立基本库存模型,给出期望利润表达式,运用极大熵准则确定需求的最可几分布,从而建立单周期产品库存模型,并得出最优订货批量。利用算例将该模型与Scarf订货规则和正态分布假设进行比较。结果表明,基于极大熵准则的库存模型能够获得更多的期望利润。     

Optimal production plan for a multi-products manufacturing system with production rate dependent failure rate

This study deals with the problem of dependence between production and failure rates in the context of a multi-product manufacturing system. It provides an answer about how to produce (i.e. the production rates) and what to produce (i.e. which product) over a finite horizon of H periods of equal length. We consider a single randomly failing and repairable manufacturing system producing two products P_a and P_b . The product P_a is produced to supply the strategic demand d(k) of the principal customer via a buffer stock S over k periods (k?=?1,?2,?…?,?H). The second product P_b is produced to meet a secondary but very profitable demand. It is produced during a given interval at the end of each period k. We develop a genetic algorithm to determine simultaneously the optimal production rate of the first product during each period k and the optimal duration of the production interval of the second product, maximising the total expected profit.     

Benefits of retailer–supplier partnership initiatives under time-varying demand: a comparative analytical study

This paper aims to help supply chain managers to determine the value of retailer–supplier partnership initiatives beyond information sharing (IS) according to their specific business environment under time-varying demand conditions. For this purpose, we use integer linear programming models to quantify the benefits that can be accrued by a retailer, a supplier and system as a whole from shift in inventory ownership and shift in decision-making power with that of IS. The results of a detailed numerical study pertaining to static time horizon reveal that the shift in inventory ownership provides system-wide cost benefits in specific settings. Particularly, when it induces the retailer to order larger quantities and the supplier also prefers such orders due to significantly high setup and shipment costs. We observe that the relative benefits of shift in decision-making power are always higher than the shift in inventory ownership under all the conditions. The value of the shift in decision-making power is greater than IS particularly when the variability of underlying demand is low and time-dependent variation in production cost is high. However, when the shipment cost is negligible and order issuing efficiency of the supplier is low, the cost benefits of shift in decision-making power beyond IS are not significant.     

An integrated optimal inventory lot-sizing and vehicle-routing model for a multisupplier single-assembler system with JIT delivery

In a manufacturing system, a just-in-time (JIT) procurement and supply system is important for reducing cost and responding to customer’s requirement quickly. Successful implementation of a JIT system needs supplier/manufacturer cooperation in small lot-size delivery and inbound logistics cost reduction. In this study, an integrated optimal model of inventory lot-sizing vehicle routing of multisupplier single-manufacturer with milk-run JIT delivery is established. A novel method for computing transportation cost is proposed. Because the integrated model is a NP-hard problem, a meta-heuristic algorithm of ant colony optimisation is developed for solving the model. Numerical examples are used to demonstrate and test the effectiveness of the model and the algorithm. The results show that integrated model with milk-run delivery can reduce the total cost and realise the JIT production and procurement philosophy which emphasises small lot-size production and delivery. The results highlight the importance of cooperation between suppliers and manufacturers in JIT production practices.