A procurement model using capacity reservation

In this paper we model a scenario where a buyer reserves capacity from one or more suppliers in the presence of demand uncertainty. We explicitly derive suppliers’ capacity reservation price, which is a function of their capacity, amount of capacity reserved by the buyer and other parameters. The buyer operates in a “built-to-order” environment and needs to decide how much capacity to reserve and from how many suppliers. For a strategy of equal allocation of capacity among the selected suppliers we develop closed form solutions and show that the model is robust to the number of suppliers from whom capacity is procured through reservation. When the parameters of demand distribution changes the supply base is likely to remain more or less the same. Our analysis further shows that increasing the number of pre-qualified suppliers does not provide significant advantages to the buyer. On the other hand, a pre-qualified supply base with greater capacity heterogeneity will benefit the buyer.     

A multi-period inventory model with multi-dimensional procurement bidding

We consider a multi-period inventory model with raw material procurements carried out via a reverse auction. Bids are multi-dimensional, and they consist of supplier information of price, shortage quantity and lead time. This work is an extension of our earlier work that has focused on multi-dimensional procurement auctions in single-period inventory models, to multi-period settings. The new model is based on a hybrid approach combining stochastic dynamic programming and simulation.     

Equilibrium strategies in random-demand procurement auctions with sunk costs

^** Email: hinz{at}ifor.math.ethz.ch We address an auction model which captures basic features ofbalancing markets for electricity. The existence and uniquenessof equilibrium are examined and a method for explicit calculationof bid strategies is presented.     

A vector-borne contamination model to assess food-borne outbreak intervention strategies

Food-borne illness occurs through the consumption of food that has been tainted at some point in the food supply chain. While most contamination is accidental, there is some evidence of intentional food adulteration. This study explores the relationship between food safety practices and consumer behavior in a two-stage food supply chain. We use a vector-borne model to represent the spread of contaminated food through the supply chain. Based on our computational study,we determine the number of consumers that become ill as a result of a contamination event, describe the effect of consumer consumption and purchase behavior on the spread of food-borne illness, and evaluate the effects of various intervention strategies on consumer illness.     

A practical exercise in simulation model validation

The validation of continuous system simulation models is a matter of great practical importance. Unfortunately, however, it often receives very little attention in university-level courses on modelling and simulation. The paper considers some possible reasons for the lack of emphasis given to model validation issues in education and describes an exercise which has been designed to introduce students to some practical aspects of internal verification and external validation of nonlinear dynamic models. The work involves a laboratory-scale system based on two inter-connected tanks of liquid and also demonstrates some important limitations of a widely-used nonlinear model. Features which make the chosen system particularly suitable for this teaching application include the relatively simple physical nature of the system and the fact that all the key variables of the model are accessible for measurement. Students are exposed to a range of practical issues, such as the selection of the sampling rate for data collection and the design of experiments to provide data sets appropriate for external validation purposes. Dealing successfully with such questions and carrying out validation tests exposes students to concepts of model credibility and the whole process of model development and application. They are also challenged in terms of their practical abilities to use computer simulation techniques and in their understanding of the mathematical model and the physics of the real system. It is argued that an exercise of this type can have very important educational benefits.     

A mathematical programming model for integrating production and procurement transport decisions

In this paper, we propose a new mathematical programming model for integrating production and procurement transport planning decisions in manufacturing systems in a unique optimization model. This problem was introduced conceptually and dubbed as MRP IV by Díaz-Madroñero et al. (2012) to extend the current MRP (material requirement planning) systems. This proposal simultaneously considers material, production resources capacities and procurement transport planning decisions with different shipping modes (such as full-truckload, less-than-truckload and milk-run) in the supply chain to avoid suboptimal results, which are usually generated due to sequential and independent plans. We considered an industrial automobile company to validate the proposed model using real world data. The results obtained by the MRP IV proposed model, in terms of total planning costs and transport efficiency indicators, are better than those obtained in the current heuristic procedures followed in the company under study.     

A Black-Scholes option pricing model with transaction costs

We consider a boundary value problem for a nonlinear differential equation which arises in an option pricing model with transaction costs. We apply the method of upper and lower solutions in order to obtain solutions for the stationary problem. Moreover, we give conditions for the existence of solutions of the general evolution equation.     

A product positioning model with costs and prices

In this paper products are conceptualized as bundles of attributes so that consumers' perceptions of existing products and their conceptions of ‘ideal’ products can be represented as points in an attribute space. Preferences are assumed to be governed by these locations.A new approach to the problem of finding an optimal position for a new product in the attribute space is presented.The sales-oriented objective function of existing models is replaced by a profit-oriented function, which explicitly observes price and positioning costs. The approach generalizes the underlying behavioral hypothesis and reduces computing time.     

An investment model with switching costs and the option to abandon

We develop a complete analysis of a general entry–exit–scrapping model. In particular, we consider an investment project that operates within a random environment and yields a payoff rate that is a function of a stochastic economic indicator such as the price of or the demand for the project’s output commodity. We assume that the investment project can operate in two modes, an “open” one and a “closed” one. The transitions from one operating mode to the other one are costly and immediate, and form a sequence of decisions made by the project’s management. We also assume that the project can be permanently abandoned at a discretionary time and at a constant sunk cost. The objective of the project’s management is to maximise the expected discounted payoff resulting from the project’s management over all switching and abandonment strategies. We derive the explicit solution to this stochastic control problem that involves impulse control as well as discretionary stopping. It turns out that this has a rather rich structure and the optimal strategy can take eight qualitatively different forms, depending on the problems data.     

Development of a three-echelon SC model to optimize coordination costs

The purpose of this study is to suggest a conceptual framework for aligning the strategic issues and the structural issues of supply chain management, and also to disclose the effect of E-business application on such an alignment. The number of suppliers, number of tiers, the level of SC integration, order penetration point, lead time, and safety stock are defined as supply chain structural issues, and the characteristics of traded products and buyer–supplier relationship are set as key strategic issues for efficient construction of supply chain structure. E-business application is designed as a moderate variable for the alignment between the strategic issues and the structural issues of supply chain management. Such effort suggests a conceptual framework required for developing an advisable set of E-business application strategies for the efficiency improvement of overall supply chain management. The empirical research model proposed in this work may be used to establish an E-supply chain progression paradigm and a new dimensional manufacturing strategy framework in the E-business era.     

On the total operating costs up to default in a renewal risk model

The paper proposes a new approach to study a general class of ruin-related quantities in the context of a renewal risk model. While the classical approaches in Sparre Andersen models have their own merits, the approach presented in this paper has its advantages from the following perspectives. (1) The underlying surplus process has the flexibility to reflect a broad range of scenarios for surplus growth including dividend policies and interest returns. (2) The solution method provides a general framework to unify a great variety of existing ruin-related quantities such as Gerber–Shiu functions and the expected present value of dividends paid up to ruin, and facilitates derivations of new ruin-related quantities such as the expected present value of total claim costs up to ruin, etc. In the end, many specific examples are explored to demonstrate its application in renewal risk models.     

A practical analytic model for predicting the performance of an encapsulated polymer composite

A novel model is presented for simulating the characteristics of a micro-encapsulated composite. The procedure initiated utilizing particle size analysis (PSA) to obtain the volume based average diameter and average spacing between the microcapsules in the composite. Results of this procedure were verified by scanning electron microscopy (SEM). Then, a simple model was presented to predict the healing percent of a triangular crack propagating in the composite. In order to obtain more detailed results, a probabilistic model was also suggested for the planar and triangular cracks, which gave the probability of crack incidence for different number of capsules to be intersected. Results of this method were then validated in comparison with the results independently obtained using a simulation by computer programming. The comparison showed close agreement between the analytical results and the simulations which present the current model and simulations as a promising method for investigating the characteristics of the encapsulated self-healing composites.     

A portfolio approach to managing procurement risk using multi-stage stochastic programming

Procurement is a critical supply chain management function that is susceptible to risk, due mainly to uncertain customer demand and purchase price volatility. A procurement approach in the form of a portfolio that incorporates the common procurement means is proposed. Such means include long-term contracts, spot procurements and option-based supply contracts. The objective is to explore possible synergies among the various procurement means, and so be able to produce optimal or near optimal results in profit while mitigating risk. The implementation of the portfolio approach is based on a multi-stage stochastic programming model in which replenishment decisions are made at various stages along a time horizon, with replenishment quantities being determined by simultaneously considering the stochastic demand and the price volatility of the spot market. The model attempts to minimise the risk exposure of procurement decisions measured as conditional value-at-risk. Numerical experiments to test the effectiveness of the proposed model are performed using demand data from a large air conditioner manufacturer in China and price volatility data from the Shanghai steel market. The results indicate that the proposed model can fairly reliably outperform other approaches, especially when either the demand and/or prices exhibit significant variability.     

A micro-movement model with Bayes estimation via filtering: Application to measuring trading noises and costs

We highlight a general hybrid system as the micromovement model for asset price using counting processes recently introduced with its Bayes estimation via filtering. We construct a new simple micromovement model and apply it to analyze trade-by-trade stock price data in the light of the series of works initiated by Christie and Schultz [Why do NASDAQ market makers avoid odd-eighth quotes?, Finance 49 (1994) 1813–1840]. Through the new model, we propose more reasonable, but computationally intensive measures for trading noise including clustering noise and non-clustering noise, and for trading cost. We employ Bayes estimation via filtering to obtain parameter estimates of the new model and to provide numerical measures of trading noise and trading cost for three stocks from four chosen periods. Our empirical results support the important findings in [Christie, Harris, Schultz, Why did NASDAQ market makers stop avoiding odd-eighth quotes?, Finance 49 (1994) 1841–1860; Barclay, Christie, Harris, Kandel, Schultz, The effects of market reform on the trading costs and depths of NASDAQ stocks, J. Finance 54(1) (1999) 1–34].     

A possibilistic mean-semivariance-entropy model for multi-period portfolio selection with transaction costs

This paper deals with a multi-period portfolio selection problem with fuzzy returns. A possibilistic mean-semivariance-entropy model for multi-period portfolio selection is presented by taking into account four criteria viz., return, risk, transaction cost and diversification degree of portfolio. In the proposed model, the return level is quantified by the possibilistic mean value of return, the risk level is characterized by the lower possibilistic semivariance of return, and the diversification degree of portfolio is measured by the originally presented possibilistic entropy. Furthermore, a hybrid intelligent algorithm is designed to obtain the optimal portfolio strategy. Finally, the comparison analysis between the possibilistic entropy model and the proportion entropy model is provided by two numerical examples to illustrate the efficiency of the proposed approaches and the designed algorithm.     

Multi-asset investment-consumption model with transaction costs

In this paper, we consider the multi-asset optimal investment-consumption model: a riskless asset and d risky assets. when the initial time is t?0, for a proportional transaction costs and discount factors, we proof that the value function of the model is a unique viscosity solution of a Hamilton-Jacobi-Bellman (HJB) equations.     

A practical model of Heineken's bottle filling line with dependent failures

This article describes a mass balance production line model based on constant machine rates, fixed finite buffer size and stochastic failure and repair behavior. Failure and repair processes need not be exponential and need not be independent. The model is easy to initialize with field data and we report favorable results from a validation exercise at Heineken Brewery. This article presents a new diagnostic for distance to infinite buffer equilibrium and a new test for independence of failure–repair processes are derived. It is shown that the stochastic fluctuations in a typical line are large, and machine unreliability can perturb the line's design.     

Piecewise lexicographic programming: A new model for practical decision problems

A new model for practical decision problems is presented. It allows one to consider lexicographic preference structures by introducing the new class of piecewise lexicographic functions which impose a total order in the objective-and-constraint space. In this way, the concepts of objective and constraints are merged into a new unified notion of co-objective. Moreover, the lexicographic preference structure may be applied not only among different coobjectives, but also among different ranges of the same decision variable. The main merits of this model appear to be its versatility (it is able to deal with different types of multiobjective optimization situations without requiring user interaction) and its compactness (it does not require one to increase the original number of decision variables and constraints). A linear version of the model is investigated in more detail.