Planning horizons for master production scheduling

Production and operations planning in organizations quite often is a multi-level sequential process, involving aggregate planning, master production scheduling, and detailed operations planning and scheduling. To obtain good planning results, it is desirable to have a proper planning horizon for each level of planning. There have been a considerable number of studies dealing with planning horizons for aggregate planning or production smoothing problems. There are also many planning horizon studies for single-item lot sizing problems. No study has addressed the issues associated with the planning horizons for master production schedules (which is a multi-item lot sizing problem in nature), particularly with respect to the relationship to the aggregate plan.This study addresses the issue of planning horizons for companies employing a make-to-stock competitive strategy facing a seasonal demand for their products. We formulate the aggregate planning problem and the master scheduling problem as two separate mathematical programs to approximate the two-stage process that typically takes place in practice. Rolling planning horizons are used to approximate the periodic updates of the plans commonly done in practice. The models also incorporate resource requirements planning concepts to estimate loads on the critical work centers.The planning process is simulated as a single pass procedure where the results of aggregate planning are passed to the master production scheduling model once per month and the results of the master scheduling model (i.e., the portion of the master schedule actually implemented) are passed back to the aggregate planning model for the next planning session.The experimental results show that when the planner faces extreme cost structures such as high smoothing costs/high setup costs or low smoothing costs/low setup costs, the planning horizon effects are reduced to a minimum. Master schedule planning horizons need not be as long as aggregate planning horizons. Alternatively, non-extreme cost structures such as high smoothing costs/low setup costs and low smoothing costs/high setup costs should be handled with equal planning horizons for both aggregate planning and master scheduling.It is also found that the firm's cost structure has an impact on the appropriate planning horizon for both aggregate planning and master scheduling. Some cost conditions allow for smaller master schedule horizons. The best horizon choice seems to be equal planning horizons for both aggregate planning and master scheduling, even though the cost savings is slight in some cases.Finally, the proper length of the planning horizon for master scheduling is affected by the planning horizon of the aggregate plans.     

Family planning in a life-cycle model with income risk

Several US states have recently restricted the access to abortions. We study fertility intentions and how family planning and abortions are used as mechanisms to control fertility among couples facing income risk. We formulate and estimate a life-cycle consumption-saving model with uninsurable income risk and imperfect contraceptive control that matches fertility behavior in the British Household Panel Survey (BHPS) well. We use the estimated model to investigate how family planning and abortions are used to control fertility in our model. Our simulations suggest that income risk affects family planning and that abortion is used to control fertility due to the presence of income risk. This indicates that the availability of abortions might play a role as an insurance mechanism.     

Assessing the effects of power grid expansion on human health externalities

Generation expansion planning is the framework under which power grid capacity expansions are made. Under this framework, mathematical optimization tools are used to determine the type of generation technology to invest in, and when and where these investments should be made in order to minimize market costs such as investment costs, fixed and variable operating & maintenance costs, and fuel costs over a long term planning horizon. Given the current infrastructure and policies, fossil fuels (such as coal, oil, and natural gas) are among the most economical sources of electricity. Thus, under these assumptions, these energy sources dominate the resulting expansion plans. However, fossil fuel combustion creates by-products contributing to ground-level ozone, particulates, and acid rain, which have harmful health implications such as premature death, respiratory-related illnesses, cardiovascular injuries, pulmonary disorders, and autism leading to lost days at school or work on a daily basis. In this research, we formulate a linear program to solve a multi-period generation expansion planning problem minimizing market costs for a centrally dispatched power system. We can then assess the human health externalities of the resulting expansion plan by studying the model output with an Environmental Protection Agency (EPA) screening tool that determines the human health externalities from the electricity sector. Results with and without emission limits and other policies can then be evaluated and compared based on predicted societal costs including human health externalities. This research enables policy makers to directly assess the health implications of power grid expansion decisions by explicitly estimating the total societal costs by quantifying externalities as part of the investment strategy.     

工程造价快速估算的数学模型及计算程序

鉴于建设工程造价具有复杂性、随机波动性、模糊性等特点,本文运用模糊数学方法,建立了工程造价快速估算的数学模型,进而阐述了工程造价快速估算的计算程序,从而为建设单位控制成本和承包单位投标报价提供决策依据和理论支持。     

Program planning with Tobit analysis—the United States food stamp case

The purpose of this paper is to illustrate the usefulness of the Tobit model in program planning. The avenue of display is the U.S. Food Stamp Program. Special analytical problems are encountered when the number of eligible nonparticipants of government programs is substantial. Under such circumstances difficulties arise with the use of ordinary regression techniques. The Tobit model is designed to reliably estimate relations from data encumbered with obstacles of this kind. Applications shown herein include program participation prediction and elasticities and probability changes associated with isolated exogenous variable changes.     

The informativeness of estimation moments

This paper introduces measures for how each moment contributes to the precision of parameter estimates in generalized method of moments settings. For example, one of the measures asks what would happen to the variance of the parameter estimates if a particular moment was dropped from the estimation. The measures are all easy to compute. We illustrate the usefulness of the measures through two simple examples as well as an application to a model of joint retirement planning of couples. We estimate the model using the British Household Panel Survey, and we find evidence of complementarities in leisure. Our sensitivity measures illustrate that the estimate of the complementarity is primarily informed by the distribution of differences in planned retirement dates. The estimated econometric model can be interpreted as a bivariate ordered-choice model that allows for simultaneity. This makes the model potentially useful in other applications.     

Land use-transport models in regional development planning

A land use-transport model of the Lowry-type is described along with several applications of the model to regional planning problems in the Toronto region of Ontario. The particular model used has several unique features. It may be disaggregated by socio-economic group, the population serving employment sub-model may be disaggregated into a number of employment sectors and transport mode-specific travel behaviour estimated. Applications of the model to public policy program formulation within the region are illustrated by three examples.     

A planning model for regional systems of CT scanners.

For the last couple of years the number of CT scanners has increased considerably in the Federal Republic of Germany. This development has led to regional disparities in the provision of CT scanner installations. For the purpose of evaluating additional locations for CT scanners a planning model is proposed. The model contains two planning options: the number of CT scanners and the regional distribution of scanner locations. It allows one to calculate overall operation costs and transportation costs, as well as additional criteria relevant to decisions about regional systems of CT scanners. The model has been applied to the northeast of Baden-Württemberg. One of the interesting findings is that an increase in the number of CT scanners may result in lower total costs for a regional system of CT scanners.     

Feasibility of national population growth targets in LDC's

This study employs a simulation model and data on desired family size to evaluate feasibility of national population growth targets. A basic claim is that neglect to consider desired family size in population planning has resulted in spurious target setting by a number of governments. It is proposed that if presently attainable family size is below desired family size in any society i, then low utilization of family planning services can be expected to continue as a function of absence of demand. Policy implications of this claim for allocation of scarce international family planning funds are discussed.     

Optimal technology choice in a dynamic-stochastic environment

The issue of technology management has become particularly relevant to operations planners as a result of the introduction of new, computer-aided process technologies in recent years. At the same time, the fields of economics and management science have developed a number of models and paradigms for technology management and equipment replacement. In this article we present a model structure that builds on this theory and that is directed toward providing insights into the particular issues associated with fixed versus variable cost trade-offs.A fairly general, dynamic, stochastic model is presented. This model links production planning with technology selection in a direct manner. The model computes optimal production plans in the face of uncertain demand in the course of evaluating the costs and benefits of each technology alternative. The key result of the article concerns conditions for the optimality of moves to lower variable cost technologies.     

What (really) accounts for the fall in hours after a technology shock?

The paper asks how state of the art DSGE models that account for the conditional response of hours following a positive neutral technology shock compare in a marginal likelihood race. To that end we construct and estimate several competing small-scale DSGE models that extend the standard real business cycle model. In particular, we identify from the literature six different hypotheses that generate the empirically observed decline in hours worked after a positive technology shock. These models alternatively exhibit (i) sticky prices; (ii) firm entry and exit with time to build; (iii) habit in consumption and costly adjustment of investment; (iv) persistence in the permanent technology shocks; (v) labor market friction with procyclical hiring costs; and (vi) Leontief production function with labor-saving technology shocks. In terms of model posterior probabilities, impulse responses, and autocorrelations, the model favored is the one that exhibits habit formation in consumption and investment adjustment costs. A robustness test shows that the sticky price model becomes as competitive as the habit formation and costly adjustment of investment model when sticky wages are included.     

Measuring the costs of children: parametric and semiparametric estimators1

How much additional income does a family with four children need to attain the same welfare level as a family with two children? And how much does a single person need compared to a childless couple? These questions are important in applied micro-economics and underlie public policy on, for example, social benefits and child allowances. In microeconomics, this is known as the problem of measuring equivalence scales. We estimate these scales using two types of subjective survey information. First, we use answers to survey questions on the income required to attain a given utility level. We compare the results for the usual linear model with semiparametric estimates, in which the functional form of the relationship between required income and family size and actual income is left unspecified. Second, we use answers to the question: how satisfied are you with actual household income? We present parametric and semiparametric estimates for ordered response models explaining this discrete variable. We find that according to the second type of information, costs of children are much larger than according to the first.     

Een systeem van kostenbeheersende productieplanning

In this paper a system of cost-controlled production planning is described. This system considers all kinds of costs associated with a production in phases (e.g. production of units, production of subassemblies, assembly) which may be affected by the planning, such as set-up costs, costs of transport, control, inventories, capacity and changes in capacity.
The mathematical model leads to a linear or mixed discrete-linear programming problem whose solution gives for each time period considered the size of the capacities which should be used and of the series of different products which should be produced. Practical recommendations are given for obtaining a sufficiently satisfying solution.     

Cost management and value creation: the missing link

Understanding of the relationship between the costs of the firm and the value the firm provides to its customers is the key to the ability of the firm to reach its profit potential. From this perspective the firm needs to have a thorough understanding of its activities, their costs and their relation to market prices. Advanced cost management studies and practices suggest a variety of different tools that help us understand the relationship between value and cost. However, most of these studies provide us with qualitative tools only. An exception is studies related to product cost planning, as in the case of target costing or value analysis/value engineering. This paper, while being a part of emerging literature on strategic cost management, extends the existing knowledge of the relationship between costs and value by introducing the value creation model (VCM). In particular, the VCM model defines the firms' cost structure in terms of value added, non-value added but required activities, as well as of waste. A firm's cost structure is aligned with value attributes embedded in products and services. The VCM model seeks to understand the trade-off between what the customer is willing to pay for a product/service bundle (value) and the cost the firm bears to provide what the customer desires. Based on these trade-offs, VCM defines value multipliers, which help the firm determine which activities the firm should focus on in order to develop a competitive advantage.     

An optimization model for the allocation of resources in family planning programs

In this paper we present a quadratic programming model for the allocation of resources in a family planning program. A quadratic cost function is minimized subject to three sets of linear constraints: one for a diffusion model of the acceptance, switching and dropout behavior of the target population; one for manpower limitations; and one for incorporating government policies on desired levels of birth rate. There are two important features to be noted. First, a recruitment cost parameter is introduced to account for the effects of market saturation on new acceptance. Second, by treating the problem as one of cost minimization rather than one of birth rate minimization, the model can be utilized to evaluate the feasibility and the minimum cost requirement of government policies on desired reductions in the birth rate. Computational considerations are also discussed.     

Nonlinear budget constraints and consumer demand: An application to public programs for residential housing

This study presents a methodology for exploiting the nonlinear hedonic nature of housing prices to estimate the compensated demands of households for particular housing attributes. The methodology is employed to provide Hicksian benefit measures of a particular housing subsidy program typical of those undertaken recently in developing countries.     

浅谈项目利润管理在销售与运作计划中的作用

目前,很多制造企业为了应对不确定的市场产品需求,加快供货速度、减少库存积压,纷纷采用S＆OP运作模式,以期达到供需平衡。如何在S＆OP运作的数据收集和评审、销售规划、供应规划、合作关系会议、高层会议等环节中预估成本、预估利润,使产品交付、销售利润最大化,是迫切需要关注和实施的问题。     

考虑实时交通情况的配送优化模型

通过分析现代物流配送的新特点、城市交通的新情况以及道路交通情况对配送计划的影响,在考虑时间窗、交通情况、车辆限制、拥挤成本等因素的基础上建立了考虑实时交通情况的配送优化模型,并介绍了模型的软件实现,分析了模型所得的结果。     

A proactive approach to supply chain risk management: Shifting orders among suppliers to mitigate the supply side risks

Globalization, e-trade, advanced technologies and emerging production techniques have increased supply chains’ efficiency and added value. However, despite numerous advantages, these factors make supply chains more fragile and vulnerable to risks. For this reason, companies that perform supply chain risk management gain competitive advantage. In the past, supply chain managers mainly focused on reducing costs; but recently, they have begun to give importance to supply chain continuity and resiliency which have significant impacts on costs as well. Hence, conventional reactive planning has given way to proactive planning in supply chain risk management. In this study, the supply chain risk management process is investigated and a procedure is proposed in the risk mitigation phase. In the first stage of the proposed procedure, an initial procurement plan is obtained via a linear programming model, considering the cost criterion as the first priority. In the second stage, this plan is revised by including the risk criterion into the planning as the second priority. The aim of this procedure that enables proactive planning is to reduce the supply side risks. The model is tested with a hypothetical data set and the cost analysis is performed to evaluate the performance of the procedure. Finally, the whole supply chain risk management process including the proposed procedure is applied to an international automotive company.     

Semiparametric identification and estimation in multi-object,English auctions

Within the independent private-values paradigm, we derive the data-generating process of winning bids for two different objects sold sequentially at English auction, assuming the valuations across objects for a particular bidder are potentially dependent. We demonstrate that, within the Archimedean family of copulas, the model is identified using only observed winning bids, and then propose a semiparametric estimation strategy to recover the joint distribution of valuations. We implement our methods using data from fish auctions held in Denmark and estimate whether bundling is expected-revenue enhancing.