Stochastic inventory problem with piecewise quadratic holding cost function containing a cost-free interval

In this paper, we consider a periodic-review stochastic inventory model with an asymmetric or piecewise-quadratic holding cost function and nonnegative production levels. It is assumed that the cost of deviating from an ideal production level or existing capacity is symmetric quadratic. It is shown that the optimal order policy is similar to the (s, S) policies found in the literature, except that the order-up-to quantity is a nonlinear function of the entering inventory level. Dynamic programming is used to derive the optimal policy. We provide numerical examples and a sensitivity analysis on the problem parameters.This research was supported by the Natural Sciences and Engineering Research Council of Canada under Grant No. A5872. The authors wish to thank an anonymous referee for very helpful comments on an earlier version of this paper.     

Block seriation problems: A unified approach. Reply to the problem of H. Garcia and J. M. Proth (Applied Stochastic Models and Data Analysis, 1, (1), 25–34 (1985))

In their article, entitled ‘Group technology in production management, the short horizon planning level’, H. Garcia and J. M. Proth have stated the following problem: starting from a (0, 1) binary matrix of size (N x M), how to divide into independent subsets the rows of this matrix simultaneously with a one-to-one corresponding partition of the columns, maximizing the presence of 1s in the intersecting blocks with a joint minimization of the presence of 0s outside of these blocks. The authors have proposed an efficient and very fast heuristic algorithm in comparison with the existing methods of a fast-growing literature on the subject. The only drawback of this algorithm is its dependence on the initial partition. In this paper, we try to improve this algorithm slightly, first in rewriting the objective function in a linear form and secondly in giving computational improvements related to this linear formulation.     

Designing two-echelon supply networks

A modern distribution network design model needs to deal with the trade-offs between a variety of factors, including (1) location and associated (fixed) operating cost of distribution centers (DCs), (2) total transportation costs, and (3) storage holding and replenishment costs at DCs and retail outlets. In addition, network design models should account for factors such as (4) stockouts, by setting appropriate levels of safety stocks, or (5) capacity concerns, which may affect operating costs in the form of congestion costs. The difficulty of making such trade-offs is compounded by the fact that even finding the optimal two-echelon inventory policy in a fixed and uncapacitated distribution network is already a hard problem. In this paper, we propose a generic modeling framework to address these issues that continues and extends a recent stream of research aimed at integrating insights from modern inventory theory into the supply chain network design domain. Our approach is flexible and general enough to incorporate a variety of important side constraints into the problem.     

Nonlinear Programming Analysis to Estimate Implicit Inventory Backorder Costs

In this paper, we use nonlinear programming to provide an alternative treatment of the economic order quantity problem with planned backorders. Many businesses, such as capital-goods firms that deal with expensive products and some service industries that cannot store their services, operate with substantial backlogs. In practical problems, it is usually very difficult to estimate accurately the values of the two types of backorder costs, i.e., the time-dependent unit backorder cost and the unit backorder cost. We redefine the original problem without including these backorder costs and construct a nonlinear programming problem with two service measure constraints which may be easier to specify than the backorder costs. We find that, with this different formulation of our new problem, we obtain results which give implicit estimates of the backorder costs. The alternative formulation provides an easier-to-use model and managerially meaningful results. Next, we show that, for a wide range of parameter values, it usually suffices to consider only one type of backorder cost, or equivalently, only one type of service measure constraint. Finally, we develop expressions which bracket the optimal values of the decision variables in a narrow range and provide a simple method for computing the optimal solution. In the most complicated case, this method requires finding the unique root of a polynomial.     

Analysis of the impact of price-sensitivity factors on the returns policy in coordinating supply chain

This paper analyzes the impact of price-sensitivity factors on characteristics of returns policy contracts in a single-period product supply chain. The contract considers stochastic and price-dependent demand. We present an analytical model and then use numerical methods with the Stackelberg game to identify the contract properties. We numerically show that a returns policy indeed improves supply chain performance. However, the benefits earned from the returns policy, under price-sensitive and variable demand, are different for different supply chain partners. First, when price-sensitivity is high, profit of the manufacturer decreases with increase in demand variability. Second, when price-sensitivity is sufficiently high and demand variability increases, the manufacturer has to surrender part of the profits to the retailer, in order to continue sales. However, even after surrendering part of the profits to the retailer, the manufacturer still earns profits that are higher than those available in a wholesale price contract. Last, from the perspective of division of channel profits, the retailer is always worse off in case of returns policies than in a wholesale price contract. Therefore, to apply this form of incentive in practice, managements should consider the impact of price-sensitivity on the returns policy and its performance.     

Integrated inventory and inspection policies for stochastic demand

In this paper, we develop integrated inventory inspection models with and without replacement of nonconforming items. Inspection policies include no inspection, sampling inspection, and 100% inspection. We consider a buyer who places an order from a supplier when his inventory level drops to a certain point, due to demand which is stochastic in nature. When a lot is received, the buyer uses some type of inspection policy. The fraction nonconforming is assumed to be a random variable following a beta distribution. The order quantity, reorder point and the inspection policy are decision variables. In the inspection policy involving determining sampling plan parameters, constraints on the buyer and manufacturer risks is set in order to obtain a fair plan for both parties. A solution procedure for determining the operating policies for inventory and inspection consisting of order quantity, sample size, and acceptance number is proposed. Numerical examples are presented to conduct a sensitivity analysis for important model parameters and to illustrate important issues about the developed models.     

A practical solution approach for the cyclic inventory routing problem

Vendor managed inventory (VMI) is an example of effective cooperation and partnering practices between up- and downstream stages in a supply chain. In VMI, the supplier takes the responsibility for replenishing his customers’ inventories based on their consumption data, with the aim of optimizing the over all distribution and inventory costs throughout the supply chain. This paper discusses the challenging optimization problem that arises in this context, known as the inventory routing problem (IRP). The objective of this IRP problem is to determine a distribution plan that minimizes average distribution and inventory costs without causing any stock-out at the customers. Deterministic constant customer demand rates are assumed and therefore, a long-term cyclical approach is adopted, integrating fleet sizing, vehicle routing, and inventory management. Further, realistic side-constraints such as limited storage capacities, driving time restrictions and constant replenishment intervals are taken into account. A heuristic solution approach is proposed, analyzed and evaluated against a comparable state-of-the-art heuristic.     

Impacts of two-stage deterioration on an integrated inventory model under trade credit and variable capacity utilization

The joint economic lot sizing problem (JELP) model provides a global view to facilitate the development of a production-inventory policy for an integrated system. However, when a deteriorating item is involved, previous studies have neglected the following two important issues: (1) the deterioration quantity increases the demand for the supplier's capacity, which consequently requires the supplier to recalculate the corresponding average cost and reevaluate the capacity utilization, and (2) given the supplier's production rate, in-transit deterioration imposes restrictions on the delivery distance or in-transit time. Therefore, the existing integrated policies may lead to infeasible solutions for the distribution channel when a deterioration item is included. In view of these two issues, a generalized JELP model under delay in payments is formulated to investigate the integrated production-inventory policy for an item with two-stage deterioration (in-transit and retail deterioration) while incorporating both transportation time and capacity utilization. By developing the average cost functions of the supply chain members and employing several new definitions (e.g., variable capacity utilization), this paper provides a mechanism for measuring the influence of two-stage deterioration on the supplier's capacity utilization for the JELP. Three algorithms are proposed to obtain optimal decisions based on the theoretical results. This paper demonstrates that the supplier's variable capacity utilization is relevant to transportation time and two-stage deterioration, which can be applied to evaluate the feasibility of the integrated production-inventory policy for the deteriorating item. Furthermore, there is a maximum allowable value for the retailer's order cycle.     

集中式供应链的生产与库存分配联合决策

考虑一个由单一制造商和多销售点构成的二级集中式供应链,制造商采用积欠订货策略生产和销售产品,因而面临生产、运输和积欠订货型库存分配与补货的联合决策问题.综合考虑了延迟交货成本、库存持有成本、运输成本和生产成本,建立了最大化总利润的非线性混合整数规划模型,以联合优化供应链的生产、运输及库存分配方案.证明了最优的产品生产分配方案应该具有的结构性质:各个销售网点在任意销售间隔期末同时出现缺货或者库存剩余.同时,提出了基于逐级求解策略的分层求解算法,保证了解的全局最优性.最后,敏感性分析表明:单位产品的库存持有成本与延迟交货成本对最优分配次数及生产量的影响作用相反,固定运输成本也会影响制造商的分配方案及生产计划,但三者均不会影响每个间隔期末的产品分配方案(分配量).     

Inventory Models with Markovian Demands and Cost Functions of Polynomial Growth

This paper studies stochastic inventory problems with unbounded Markovian demands, ordering costs that are lower semicontinuous, and inventory/backlog (or surplus) costs that are lower semicontinuous with polynomial growth. Finite-horizon problems, stationary and nonstationary discounted-cost infinite-horizon problems, and stationary long-run average-cost problems are addressed. Existence of optimal Markov or feedback policies is established. Furthermore, optimality of (s, S)-type policies is proved when, in addition, the ordering cost consists of fixed and proportional cost components and the surplus cost is convex.