Renewal theory forecasting for stock control

A method is described for forecasting spares demand from data on model sales. The method uses concepts borrowed from renewal theory. The scheme is particularly useful for producing a forecast of all-time future demand for a spare so that a decision may be made about the timing of the final production run.     

Solving a bi-criterion cutting stock problem with open-ended demand: a case study

We consider a real-life cutting stock problem with two types of orders. All orders have to be cut from a given number of raws (also known as stock unit, master reel or jumbo). For each order the width of the final (also known as reels or units) and the number of finals is given. An order is called an exact order when the given number of finals must be produced exactly. An order is called an open order when at least the given number of finals must be produced. There is a given maximum on the number of finals that can be produced from a single raw which is determined by the number of knives on the machine. A pattern specifies the number of finals of a given width that will be produced from one raw. A solution consists of specifying a pattern for each raw such that in total the number of finals of exact orders is produced exactly and at least the number of finals of open orders is produced. There are two criteria defined for a solution. One criterion is the cutting loss: the total width of the raws minus the total width of the produced finals. The second criterion is the number of different patterns used in the solution. We describe a branch-and-bound algorithm that produces all Pareto-optimal solutions.     

Pairs trading and outranking: The multi-step-ahead forecasting case

Pairs trading is a popular speculation strategy. Several implementation methods are proposed in the literature: they can be based on a distance criterion or on co-integration. This article extends previous research in another direction: the combination of forecasting techniques (Neural Networks) and multi-criteria decision making methods (Electre III). The key contribution of this paper is the introduction of multi-step-ahead forecasts. It leads to major changes in the trading system and raises new empirical and methodological questions. The results of an application based on S&P 100 Index stocks are promising: this methodology could be a powerful tool for pairs selection in a highly non-linear environment.     

Dividends as a signalling mechanism: the case of illiquid stock markets

^** Email: maximiliano.gonzalez{at}iesa.edu.ve Dividends payment is an important signalling device used bycorporations. Through the dividend policy, firms can ‘separate’themselves and let the market, in an environment of asymmetricinformation, correctly assess their value. However, it is notclear that this mechanism is effective in markets subject toliquidity shocks. We addressed this problem by developing amodel where liquidity shocks occur with a certain probabilityand the stockholder must sell some illiquid assets at a discountin order to cover his cash needs. The results show that undercertain conditions and except for the very extreme cases, dividendsin fact can still be used as a signalling mechanism by companiesin illiquid markets.     

Age-based vs. stock level control policies for a perishable inventory system

In this study, we investigate the impact of modified lotsize-reorder control policy for perishables which bases replenishment decisions on both the inventory level and the remaining lifetimes of items in stock. We derive the expressions for the key operating characteristics of a lost sales perishable inventory model, operating under the proposed age-based policy, and examine the sensitivity of the optimal policy parameters with respect to various system parameters. We compare the performance of the suggested policy to that of the classical (Q,r) type policy through a numerical study over a wide range of system parameters. Our findings indicate that the age-based policy is superior to the stock level policy for slow moving perishable inventory systems with high service levels.     

Experimental study of a Bayesian method for daily electricity load forecasting

The method of Bayesian model discrimination is investigated for the possible contributions it may provide in the area of automatically forecasting the daily electricity demand cycle. A set of differing demand models have probabilities attached to them in such a way that these would be continuously updated with the available data and the actual forecasts obtained as expectations across all the models. Simulation experiments indicate significantly improved forecasting performance over a commonly used rescaling type of approach. Some practical issues in implementation are discussed.     

Cross-correlations between volatility,volatility persistence and stock market integration: the case of emergent stock markets

In this paper, we investigate the dynamics of the two pairs of relationship, respectively volatility/market integration and volatility persistence/market integration, in the case of 20 emerging stock markets during the period 1999–2013. Employing the rolling windows approach we find that on most markets the persistent positive trend in volatility and volatility persistence is associated with the same trend in market integration. We use the detrending moving-average cross-correlation coefficients and we find positive cross-correlation that appears particularly in the long term and can only partly be attributed to the global financial crisis. The cross-section analysis shows that the markets which are more integrated display stronger volatility and volatility persistence, especially after 2005, when the level of market integration is higher. Our findings have several important implications for international portfolio management and security valuation.     

Optimal control of an elastic crane-trolley-load system - a case study for optimal control of coupled ODE-PDE systems

We present a mathematical model of a crane-trolley-load model, where the crane beam is subject to the partial differential equation (PDE) of static linear elasticity and the motion of the load is described by the dynamics of a pendulum that is fixed to a trolley moving along the crane beam. The resulting problem serves as a case study for optimal control of fully coupled partial and ordinary differential equations (ODEs). This particular type of coupled systems arises from many applications involving mechanical multi-body systems. We motivate the coupled ODE-PDE model, show its analytical well-posedness locally in time and examine the corresponding optimal control problem numerically by means of a projected gradient method with Broyden-Fletcher-Goldfarb-Shanno (BFGS) update.     

A case study on the shareholder network effect of stock market data: An SARMA approach

One of the key research problems in financial markets is the investigation of inter-stock dependence. A good understanding in this regard is crucial for portfolio optimization. To this end, various econometric models have been proposed. Most of them assume that the random noise associated with each subject is independent. However, dependence might still exist within this random noise. Ignoring this valuable information might lead to biased estimations and inaccurate predictions. In this article, we study a spatial autoregressive moving average model with exogenous covariates. Spatial dependence from both response and random noise is considered simultaneously. A quasi-maximum likelihood estimator is developed, and the estimated parameters are shown to be consistent and asymptotically normal. We then conduct an extensive analysis of the proposed method by applying it to the Chinese stock market data.

     

Breadth of range and depth of stock: forecasting and inventory management at Euro Car Parts Ltd.

This paper investigates inventory management issues in a distribution network. The study is motivated by examining the operation of a wholesaling car parts company. Customer service requirements are of paramount importance in this market sector. The nature of the demand facing the company is characterised. The breadth of range of stock keeping units (SKUs) held at a stocking location and the quantity of each SKU held are normally treated in isolation but in this case, the rule developed to select the range of SKU was extended to determine the level of stock to hold. It is intuitively obvious that these two factors should be linked, yet the authors have not found any other literature developing the connection in a practical context. Forecasting issues are explored as the rule on stock range depends on a forecast of the number of orders received for each SKU at each stocking unit. Some implementation issues and extensions are indicated.     

Computational study of a column generation algorithm for bin packing and cutting stock problems

This paper reports on our attempt to design an efficient exact algorithm based on column generation for the cutting stock problem. The main focus of the research is to study the extend to which standard branch-and-bound enhancement features such as variable fixing, the tightening of the formulation with cutting planes, early branching, and rounding heuristics can be usefully incorporated in a branch-and-price algorithm. We review and compare lower bounds for the cutting stock problem. We propose a pseudo-polynomial heuristic. We discuss the implementation of the important features of the integer programming column generation algorithm and, in particular, the implementation of the branching scheme. Our computational results demonstrate the efficiency of the resulting algorithm for various classes of bin packing and cutting stock problems. Received October 18, 1996 / Revised version received May 14, 1998?Published online July 19, 1999     

BPPLIB: a library for bin packing and cutting stock problems

The bin packing problem (and its variant, the cutting stock problem) is among the most intensively studied combinatorial optimization problems. We present a library of computer codes, benchmark instances, and pointers to relevant articles for these two problems. The library is available at http://or.dei.unibo.it/library/bpplib. The computer code section includes twelve programs: seven are directly downloadable from the library page, while for the remaining five we provide addresses where they can be obtained or downloaded. Some of the codes for which we provide an original C++ implementation need an integer linear programming solver. For such cases, the library provides two versions: one that uses the commercial solver CPLEX, and one that uses the freeware solver SCIP. The benchmark section provides over six thousands instances (partly coming from the literature and partly randomly generated), together with the corresponding solutions. Instances that are difficult to solve to proven optimality are included. The library also includes a BibTeX file of more than 150 references on this topic and an interactive visual tool to manually solve bin packing and cutting stock instances. We conclude this work by reporting the results of new computational experiments on a number of computer codes and benchmark instances.     

Construction and selection of quantitative planning models — a general procedure illustrated with models for stock control

The paper investigates the process of quantitative model construction when for a particular realworld decision problem different quantitative models are available. It develops first some general features for constructing a model hierarchy comprising all quantitative models which should be taken into consideration. The main objective is an investigation into the selection process giving the best quantitative model for the particular decision problem at hand. This selection, however, can be performed in different ways possibly ending up with different models. A myopic selection principle is suggested which leads to a class of strategies. Different strategies within this class are discussed showing the complexity of the selection procedure. The investigations are illustrated using inventory models particularly stressing the role of cost parameters.     

Process-oriented knowledge management: a case study

Most knowledge repositories store documents organized by subject areas. In process-oriented knowledge management, each knowledge management project is developed around an organizational process and the mission, rationale and objectives of the process define the scope of the project. At the heart of the process-oriented knowledge management strategy is a knowledge management system called KMS. KMS has a workflow management subsystem that enables it to capture knowledge in context as it is created and present knowledge to the user at the right step of the process. Its repository contains not only knowledge created and manipulated in an organizational process, but also the knowledge of the process itself in the form of process designs, case histories and lessons learned from past experiences. This paper describes the process-oriented knowledge management strategy and its implementation in the real estate organization of a real-life global company.     

Systemic risk assessment: a case study

Project Risk Registers have been used extensively for many years. However, they do not account for the interaction between risks, for example, the occurrence of one risk exacerbating other risks or portfolios of risks being more significant than the sum of the individual risks. This leads to the need to consider ‘risk systemicity’ as a part of risk analysis. This paper reports on a specific case for a large multinational project based organization, one that the authors had been involved with in the analysis of a number of projects that had massive cost overruns. Following these analyses the organization was persuaded of the importance of risk systemicity. The organization therefore engaged the authors to develop a ‘Risk Filter’. This filter is a tool for identifying areas of risk exposure on future projects and creating a framework for their investigation. The ‘Risk Filter’ is now used on all projects ever since its introduction; by the end of May 2003 it had been used by nine divisions, on over 60 major projects, and completed by 450 respondents. It is also used at several stages during the life of a project to aid in the risk assessment and management of each project, and contributes to a project database.     

Workforce-constrained maintenance scheduling for military aircraft fleet: a case study

The problem is related to a fleet of military aircraft with a certain flying program in which the availability of the aircraft sufficient to meet the flying program is a challenging issue. During the pre- or after-flight inspections, some component failures of the aircraft may be found. In such cases, the aircraft are sent to the repair shop to be scheduled for maintenance jobs, consisting of failure repairs or preventive maintenance tasks. The objective is to schedule the jobs in such a way that sufficient number of aircrafts is available for the next flight programs. The main resource, as well as the main constraint, in the shop is skilled-workforce. The problem is formulated as a mixed-integer mathematical programming model in which the network flow structure is used to simulate the flow of aircraft between missions, hanger and repair shop. The proposed model is solved using the classical Branch-and-Bound method and its performance is verified and analyzed in terms of a number of test problems adopted from the real data. The results empirically supported practical utility of the proposed model.     

A deterministic resource scheduling model in epidemic control: A case study

The resources available to tackle an epidemic infection are usually limited, while the time and effort required to control it are increasing functions of the starting time of the containment effort. The problem of scheduling limited available resources, when there are several areas where the population is infected, is considered. A deterministic model, appropriate for large populations, where random interactions can be averaged out, is used for the epidemic’s rate of spread. The problem is tackled using the concept of deteriorating jobs, i.e. the model represents increasing loss rate as more susceptibles become infected, and increasing time and effort needed for the epidemic’s containment. A case study for a proposed application of the model in the case of the mass vaccination against A(H1N1)_v influenza in the Attica region, Greece and a comparative study of the model’s performance vs. the applied random practice are presented.     

Choosing a random spanning subtree: a case study

Broder⁽⁴⁾ has suggested a stochastic algorithm for generating a random spanning subtree of a graph. This paper studies this algorithm for a special class of graphs. A complete spectral decomposition of the associated Markov chain is given. The analysis available from this is compared to stopping-time techniques and purely geometric bounds on the second eigenvalue.     

Computational study of the US stock market evolution: a rank correlation-based network model

This paper presents a computational study of global characteristics of the US stock market using a network-based model referred to as the market graph. The market graph reflects similarity patterns between stock return fluctuations via linking pairs of stocks that exhibit “coordinated” behavior over a specified period of time. We utilized Spearman rank correlation as a measure of similarity between stocks and considered the evolution of the market graph over the recent decade between 2001–2011. The observed market graph characteristics reveal interesting trends in the stock market over time, as well as allow one to use this model to identify cohesive clusters of stocks in the market.