Lot sizing in workload control systems

An important basis for workload control (WLC) is the existence of functional relationships between the mean level of work-in-process (WIP) and the values of important goal variables, like average flow time, capacity utilization, etc. These functional relationships are largely influenced by the lot sizes. This means that the usual objective of lot sizing must be supplemented by considering the impact of lot sizes on the relationships between WIP and the other goal variables. Here it is shown that this insight leads to flow time oriented lot sizing models. This type of lot sizing models is analysed. It is argued that the derivation of simple rules for lot sizing is an important research topic, and a model for deriving such rules is presented. Some rules are derived from the model, assuming that the batches are processed by an M/G/1 server, and it is shown that these rules support insights based on simulation in the 1980s. Topics for future research are outlined as well.     

随机需求下期权采购与预售联合决策研究

市场波动几乎是每一个企业都必须面临的问题.尤其对于产品提前期长而销售期相对较短的零售企业或新产品上市企业来说,市场波动所导致的产品短缺和库存积压为企业的经营带来了巨大的挑战.基于此,如何降低市场波动所带来的风险便成为运营管理领域讨论的热门话题.目前,学术界和企业界提出了许多降低市场波动风险的策略,归纳起来大致有两个方面...     

需求不确定下的补偿策略理论模型

在需求不确定的前提条件下就供应商对销售商的补偿策略进行了深入研究,建立了包 含风险偏好的补偿策略理论模型. 在该理论模型的基础上,运用数值分析的手段分析了风险偏 好对供应链中参与者决策行为的影响,为供应链决策者制定合理的决策提供了科学依据. 最 后,结合我国国情,重点讨论如何在我国正确实施补偿策略.     

Strategic supply network planning with vendor selection under consideration of risk and demand uncertainty

We present a stochastic version of a three-layer supply network planning problem that includes the selection of vendors that must be equipped with company-specific tools. The configuration of a supply network must be determined by using demand forecasts for a long planning horizon to meet a given service level. The risk induced by the uncertain demand is explicitly considered by incorporating the conditional value at risk. The objective is to maximize the weighted sum of the expected net present value of discounted cash flows and the conditional value at risk. This would lead to a non-linear model formulation that is approximated by a mixed-integer linear model. This approximation is realized by a piecewise linearization of the expected backlogs and physical inventory as non-linear functions of cumulative production quantities. A two-stage stochastic programming approach is proposed. Our numerical analysis of generic test instances indicates that solving the linearized model formulation yields a robust and stable supply network configuration when demand is uncertain.     

A column generation heuristic for dynamic capacitated lot sizing with random demand under a fill rate constraint

This paper deals with the dynamic multi-item capacitated lot-sizing problem under random period demands (SCLSP). Unfilled demands are backordered and a fill rate constraint is in effect. It is assumed that, according to the static-uncertainty strategy of Bookbinder and Tan [1], all decisions concerning the time and the production quantities are made in advance for the entire planning horizon regardless of the realization of the demands. The problem is approximated with the set partitioning model and a heuristic solution procedure that combines column generation and the recently developed _ABCβ${\mathit{ABC}}_{\beta }$ heuristic is proposed.     

Lot sizing and scheduling: a survey of practices in Brazilian companies

The lot sizing and scheduling (LSS) problem has motivated much research in production planning and control. However, while there are many papers on modelling this problem, there is scant research on how it is addressed in the industry. We present a survey of Brazilian industry practices in LSS, intending to understand the problem faced by operations managers, drawing parallels with academic findings to identify gaps between theory and practice and opportunities for future research. We confirm that the main objective of practitioners in companies operating under MTS strategy is to maximise service level, followed by inventory reduction. Availability of raw material, demand uncertainty and safety stock levels, lack of decision support software and the impact of sequence-dependent set-up times are other major concerns highlighted by the practitioners. Lastly, we confirmed that despite the relevant body of research on this problem, there is still a large gap between theory and practice.     

Lot sizing in case of defective items with investments to increase the speed of quality control

In many cases the quality of each item in a lot is checked. Speeding up the quality checking process increases the responsiveness of the system and saves cost. The percentage of defective items is a random variable and two models are proposed. In one of the models the system remains always at the same state, while in the other one after each order cycle, the state of the system may change, thus the percentage of defective items may be different in consecutive periods. In both cases the speed of the quality checking is a variable, and procedures are provided to find the optimal lot sizes and screening speed for general and specific investment cost functions. The characteristics of the two model settings will largely be different when the percentage of defective items is high. Among the important managerial insights gained is that a high unit backlogging cost, especially spurs the system to invest more intensively into improving the quality checking process.     

Resilience metrics in the assessment of complex supply-chains performance operating under demand uncertainty

The design and planning of resilient supply chains is a major challenge due to the increasing complexity of these systems that operate in a global market and therefore are more exposed to disruptions. In the present work a design and planning model that integrates demand uncertainty is applied to five supply chain structures that are submitted to different types of disruptions. Disruptions are modelled in a probabilistic manner, resulting in the incorporation of two sources of uncertainty. Eleven indicators are considered to assess the supply chains’ resilience, which comprise network design, centralization and operational indicators. The goal is to provide managers what are expected operational impacts (measured by the operational indicators) by assessing the behavior of network and centralization indicators and their known resilience behaviors from the literature. A case study of a European supply chain is used to illustrate the methodology and a discussion on the results obtained is presented in order to conclude which main characteristics a manager should consider when designing and planning resilient supply chains.     

The impact of component commonality in an assemble-to-order environment under supply and demand uncertainty

A material requirements planning simulator with a two-level bill-of-material is used to study the impact of introducing component commonality into an assemble-to-order environment when demand is subject to random variations, and component procurement orders experience random delays. By using simulated data, our ANOVA results show that component commonality significantly interacts with existence of demand and supply chain uncertainties, and benefits of component commonality are most pronounced when both uncertainties exist.     

Location-boundedness,investment irreversibility,and divestment of international joint ventures under host market demand uncertainty

We employ the real options perspective to examine how the irreversibility of location-bound assets and resources affects the divestment of international joint ventures (IJVs) under exogenous uncertainty in host countries. Utilizing a large sample of Korean IJVs and addressing a sample selection of IJVs and the endogeneity of firms’ choice of location-bound investments, we find that high host market demand uncertainty interacts with localized products or local sales forces and reduces divestment rates of IJVs. We also find that the deterrent effects of these two country-specific investments are more salient for IJVs with local sourcing and sales. These findings imply that the deterrent effect of location-boundedness is congruent with the uncertainty-based real options theory when explaining IJV divestment.     

Optimal lot sizing under continuous price decrease

An important characteristic of high-tech industries is decreasing component prices over time. In the personal computer industry, some component prices decline at a rate of 1% per week. This paper develops an inventory model for products experiencing continuous decrease in unit price. We develop an accurate closed-form approximate solution to the model. Our results indicate that declining prices lead to substantial decrease in the optimal cycle time and much frequent ordering. This explains the heavy emphasis on just-in-time inventory management practiced by successful companies in high-tech industries. While previous models attributed the success of just-in-time policies to reduced holding cost and improved quality, under declining prices a substantial source of savings becomes lower costs of raw materials which is significant part of cost in these industries. We illustrate the results of the model with a numerical example and perform sensitivity analysis.     

A decision support system for a third-party coordinator managing supply chain with demand uncertainty

Global supply chains reduce cost but increase lead times, complexities and uncertainties. Retailers in consumer products industry are getting shorter lead time to respond to market demand. To meet this challenge, many rely on third party supply chain managers (SCMs) for economically supplying required quantities of finished products quickly. However, due to shorter ‘time to market’, the SCM has to procure raw materials and start production process based on expected demand. Since SCM absorbs financial penalties associated with under- and over-estimation of demand from retailer, finding an optimal production lot size and product customisation strategy are essential to an SCM's operation. We develop a profit maximisation model and provide a close-form solution that allows an SCM to calculate optimal production lot size. The model is used to examine profitability of postponing product customisation. Finally, the effect of demand variation on SCM's profitability is explored.     

Combined demand and lead time uncertainty with back-ordering in a multi-level product structure environment

The performance of two lot-sizing algorithms incorporating back-orders is evaluated and compared with several traditional lot-sizing rules. This comparison is undertaken for a multi-level product structure environment operating under a rolling horizon in the presence of both demand and lead time uncertainties. By means of simulation and statistical analysis of the simulation output, the impact on system performance of a variety of demand and lead time scenarios, product structures, cost parameters and lot-sizing, is evaluated. The conclusions drawn emphasize important differences in the influence of the factors on system performance given the presence or absence of uncertainty.     

Production lot sizing with process deterioration and machine breakdown under inspection schedule

The paper develops integrated production, inventory and maintenance models for a deteriorating production system in which the production facility may not only shift from an ‘in-control’ state to an ‘out-of-control’ state but also may break down at any random point in time during a production run. In case of machine breakdown, production of the interrupted lot is aborted and a new production lot is started when the on-hand inventory is depleted after corrective repair. The process is inspected during each production run to examine the state of the production process. If it is found in the ‘in-control’ state then either (a) no action is taken except at the time of last inspection where preventive maintenance is done (inspection policy-I) or (b) preventive maintenance is performed (inspection policy-II). If, however, the process is found to be in the ‘out-of-control’ state at any inspection then restoration is done. The proposed models are formulated under general shift, breakdown and repair time distributions. As it is, in general, difficult to find the optimal production policy under inspection policy-I, a suboptimal production policy is derived. Numerical examples are taken to determine numerically the optimal/suboptimal production policies of the proposed models, to examine the sensitivity of important model parameters and to compare the performance of inspection and no inspection policies.     

Measures of return under uncertainty

The purpose of this paper is twofold. First a methodlogy for contrasting accounting and economic measures of return will be briefly described. This methodology overcomes many of the limitations of previous comparisons of these measures. Second, the results of applying the new methodology to an area of current accounting concern—adjusting for price level changes—will be presented.     

Multiobjective investment planning under uncertainty

In this paper we consider the relevance of various planning methods and decision criteria to multiobjective investment planning under uncertainty. Assuming that a natural reaction to uncertainty is to operate so as to leave open as many good options as possible (as opposed to maximizing subjective expected utility) we argue that the planning process should concentrate on analyzing the effects of the initial decision, and that for this exercise the classical methods of mixed integer programming are inappropriate. We demonstrate how the technique of dynamic programming can be extended to take account of multiple objectives and use dynamic programming as a framework in which we analyze the robustness of an initial decision in the face of various types of uncertainty. In so doing we also analyze the risks involved in both the planning and decision making functions.     

Economic Lot Scheduling Problem with Returns

Motivated by a case study of a company that produces car parts, we study the multi‐product economic lot scheduling problem for a hybrid production line with manufacturing of new products and remanufacturing of returned products. For this economic lot scheduling problem with returns (ELSPR), we consider policies with a common cycle time for all products, and with one manufacturing lot and one remanufacturing lot for each product during a cycle. For a given cycle time, the problem is formulated as a mixed integer linear programming (MIP) problem, which provides the basis for an exact solution. The application of this model for one of the core products of the case study company indicates a 16% reduction in cost compared to the current lot scheduling policy.     

道德风险下带有Knight不确定的最优动态契约设计

本文从概率统计模型本身的不确定性是本质的、不能消除掉的角度出发, 研究了Knight不确定下连续时间委托-代理问题, 其中主要考虑了代理人的道德风险对契约执行过程以及契约存续情况的影响.首先, 建立了代理人延续价值以及委托人预期利润的动态方程.其次, 运用次线性期望下的随机最优性原理, 以更加准确、深刻的方法去刻画实际委托人和代理人经济行为, 进而得到委托人效用值函数的Hamilton-Jacobi-Bellman (HJB) 方程, 并求得委托人对代理人最优支付以及代理人最优努力水平的表达式.最后, 通过理论解的数值模拟, 分析了Knight不确定对委托人和代理人最优策略以及最优契约的影响.     

Disassembly to order system under uncertainty

This paper presents a multi-criteria optimization model of a disassembly-to-order (DTO) system under uncertainty. The goal of the proposed model is to determine the best combination of the number of each product type to be taken back from the last user and/or collectors. The EOL products are then disassembled for the retrieval of reusable components and materials and resold in order to meet a certain level of demand under a variety of physical, financial and environmental constraints. The surplus components are recycled, stored for usage in subsequent periods or properly disposed. The problem is modeled as a multi-criteria decision-making problem under uncertainty, where the aspiration levels for various goals are more likely to be in the “approximately more (less) than” and/or “more (less) is better” form. We employ fuzzy goal programming technique to solve the problem. When solved, the model provides the number of EOL products to be taken back as well as the number of items reused, recycled, stored and disposed. The values of a host of other performance measures are also obtained, including total profit, materials and items sales revenues, take back cost, transportation costs as well as costs of preparation of EOL products, destructive disassembly, non-destructive disassembly, recycling, storage and disposal. A case example is presented to illustrate the model's implementation.