Integrated planning of acquisition,disassembly and bulk recycling: a case study on electronic scrap recovery

Abstract. Due to national and supranational legislation activities, the recovery of discarded products will attain an increasing momentum. Electronic equipment consists of many different parts and materials. Therefore, the related recovery process is often divided into disassembly to remove harmful substances or reusable parts and into bulk recycling to recover ferrous and non-ferrous metals. In order to consider the interactions between choice of scrap to be recovered (acquisition problem), disassembly and bulk recycling, a mixed-integer linear programming model for integrated planning of these stages is presented in this case study. It is applied to determine the daily allocation of products to processes for a major electronic scrap recovery centre that faces limited processing capacities and market restrictions. The optimization calculations covering typical discarded electronic products to be recycled in the related centre lead to a relevant improvement of the economic success. RID="*" ID="*" The authors would like to thank the German “Bundesministerium für Bildung und Forschung” (Federal Ministry of Education and Research) for supporting the research project “Substance Flow Oriented Closed Loop Supply Chain Management in the Electrical and Electronic Equipment Industry (STREAM)rdquo;. Correspondence to: T. Spengler     

An MILP-based approach to the short-term scheduling of make-and-pack continuous production plants

Many fast moving consumers good manufacturing companies produce a moderate number of intermediates that are combined in many different ways to generate an enormous variety of end products. To do that, such companies usually run continuous production plants in a make-to-stock environment. The process structure includes a fabrication area yielding basic intermediates that are stocked in a large middle storage space, and a packing sector where finished products usually comprising several intermediates are manufactured. Intermediates all undergo the same sequence of processing stages and the production of any campaign is sequentially allocated to an ordered set of end products. An MILP continuous time scheduling problem formulation handling independently assignment and sequencing decisions and considering sequence-dependent setup times and specific due dates for export orders has been developed. The problem objective is to meet all end-product demands at minimum make-span. The proposed model is able to account for assorted products, multiple campaigns for a particular intermediate even at the same unit and the consecutive allocation of an intermediate campaign to different finished products. Moreover, it can easily embed powerful preordering rules to yielding reduced MILP formulations so as to tackle real-world industrial problems at low computational cost. The approach has been successfully applied to large-scale industrial examples. RID="*" ID="*" The authors acknowledge financial support from FONCYT under Grant 14-07004, and from “Universidad Nacional del Litoral” under CAI+D 121. Correspondence to: J. Cerdá     

Reduced outpatient waiting times with improved appointment scheduling: a simulation modelling approach

Abstract. An outpatient department represents a complex system through which many patients with varying needs pass each day. An effective appointment system is a critical component in controlling patient waiting times within clinic sessions. Current waiting times are often unacceptable and place great stress on clinic staff. This paper describes the development and use of a detailed simulation model of an Ear, Nose and Throat (ENT) outpatient department. The simulation allows various appointment schedules to be examined and their effects on the clinic evaluated. The model has been used to identify a number of critical factors that influence patient waiting times and the build up of queues in the clinic. Alternative appointment schedules have been shown to drastically reduce patient waiting times, without the need for extra resources, and enable the department to move towards meeting the UK Government's Patient's Charter. RID="*" ID="*" The authors would like to express their thanks for the valuable support provided by the anonymous participants (outpatient department staff). Thanks also to Helen Gilby, Dr Arjan Shahani and Professor Valter de Senna for their useful comments and help during the research. Correspondence to: P.R. Harper     

An integrated system solution for supply chain optimization in the chemical process industry

This paper considers a complex scheduling problem in the chemical process industry involving batch production. The application described comprises a network of production plants with interdependent production schedules, multi-stage production at multi-purpose facilities, and chain production. The paper addresses three distinct aspects: (i) a scheduling solution obtained from a genetic algorithm based optimizer, (ii) a mechanism for collaborative planning among the involved plants, and (iii) a tool for manual updates and schedule changes. The tailor made optimization algorithm simultaneously considers alternative production paths and facility selection as well as product and resource specific parameters such as batch sizes, and setup and cleanup times. The collaborative planning concept allows all the plants to work simultaneously as partners in a supply chain resulting in higher transparency, greater flexibility, and reduced response time as a whole. The user interface supports monitoring production schedules graphically and provides custom-built utilities for manual changes to the production schedule, investigation of various what-if scenarios, and marketing queries. RID="*" ID="*" The authors would like to thank Hans-Otto Günther and Roland Heilmann for helpful comments on draft versions of this paper.     

Modelling the effects of the Austrian inpatient reimbursement system on length-of-stay distributions

Abstract. This paper analyses the effects of the new Austrian performance-oriented inpatient payment system on discharge strategies of hospitals by investigating length-of-stay (LOS) distributions. Using generalised linear models applied to data from 1998, we calculate the impact of day and month of admission as well as types of admission and discharge on the LOS of inpatients with major diagnoses. Hereby, we prove significant interdependencies among these variables and reveal hospital behaviour such as 1) premature discharges of inpatients or “unbundling” and 2) “patient splitting”. Hence, our findings illustrate that hospitals react to incentives set by the new system in order to maximise their revenues. Hence, the current reimbursement system still has potential for cost reduction while maintaining high quality of health care. Our strategic policy model supports decision makers in disclosing these effects and provides policy implications to close exploitable gaps within the new reimbursement system. RID="We are grateful to experts of the federal funds and the Ministry of Labour, Health and Social Affairs for providing us with detailed information on the Austrian reimbursement system for inpatients and for approving our data request. In addition, we especially thank Dr. Wilhelm Frank of the Austrian Federal Institute for Health Care for making the needed inpatient data available for us. Special thanks are due to Professor Arjan Shahani, Paul Harper and Sally Brailsford (University of Southampton, United Kingdom), Professor Lucas Delesie (Catholic University of Leuven, Belgium), Professor Bernhard Schwarz (University of Vienna, Austria) and Professor Engelbert Dockner (University of Vienna, Austria) for valuable comments on this investigation. Correspondence to:M. Rauner     

Portfolio management in the binomial model: conditions for outperforming benchmarks

The performance of a portfolio manager is in practice usually measured by the result of his trading strategy compared to a benchmark. Therefore the information whether there exists a strategy that allows to outperform the benchmark is of high value for an active investor. The article shows how this information can be generated in the binomial model. In this context the connection between trading strategies and the investor's expectations concerning future asset prices is analyzed. Based on these findings several conditions are derived that allow the portfolio manager to judge whether the benchmark can be outperformed by an active trading strategy. RID="*" ID="*" Thomas Balzer now works in the Risk Measurement & Management Department of Credit Suisse First Boston in London. The views expressed in this article are those of the author, and do not necessarily represent those of Credit Suisse Group or Credit Suisse First Boston. The author thanks Dr. Michael Olbrich for careful reading and several useful comments.     

Analysis of a single stage production system with heterogeneous machines

The performance of a single stage production system with two heterogeneous machines and two classes of jobs is investigated. The machines have a common buffer with jobs of both classes waiting for service. The arrivals are assumed to follow a Poisson process and the service times to be distributed exponentially. The evaluated production system differs from a classical homogeneous multiple server queueing system with regard to inhomogeneities of the two machines. Time inhomogeneity – the service times of the two machines being unequal – and functional inhomogeneity – one of the machines can handle only one class (A) of jobs – are to be distinguished. In the case of time inhomogeneity the calculation of system performance parameters may be carried out using an explicit formula, whereas for the analysis of functional inhomogeneity a numerical solution has to be derived. The impact of time inhomogeneity is very small and decreases with the system workload. On the contrary, functional inhomogeneity leads to elevated cycle times of up to 40% depending on the degree of inhomogeneity (measured by the fraction of A jobs) and the workload. Therefore, in contrast to the time-inhomogeneous case, single stage production systems with functional inhomogeneity can only be approximated tolerably by a homogeneous multiple server queueing system if the fraction of one-machine jobs is less than 30%. The increased throughput times above 30% are supplied by the diagram developed from the numerical solutions. RID="*" ID="*" While this research was constructed the author was affiliated to Institute of Conveying Technology and Logistics. Correspondence to: C. R. Lippolt     

A scheduling method for Berth and Quay cranes

This paper discusses a method for scheduling Berth and Quay cranes, which are critical resources in port container terminals. An integer programming model is formulated by considering various practical constraints. A two-phase solution procedure is suggested for solving the mathematical model. The first phase determines the Berthing position and time of each vessel as well as the number of cranes assigned to each vessel at each time segment. The subgradient optimization technique is applied to obtain a near-optimal solution of the first phase. In the second phase, a detailed schedule for each Quay crane is constructed based on the solution found from the first phase. The dynamic programming technique is applied to solve the problem of the second phase. A numerical experiment was conducted to test the performance of the suggested algorithms. RID="*" ID="*" This research has been supported in part by Brain Korea 21 Program (1999–2002). Correspondence to: Y.-M. Park     

On the steady state of the replicating portfolio: accounting for a growth rate

For the risk management and transfer pricing of non-maturity liabilities, banks in Europe often use a so-called replicating portfolio technique. A commonly used implementation is replication of a fixed investment rule every time period. This paper deals with the development of the portfolio in the long run, when using this methodology. Applying this replicating portfolio technique yields, after a while, a steady state. Besides the straightforward result when volume is constant, we solve the steady states for the case where the funds (volume) grow with a fixed rate (e.g. due to credited interest or growth in GDP). We therefore define a system growth process, alternative to the Markov process (when volume is constant). From a transfer pricing and risk-management point of view, the resulting portfolio should satisfy certain requirements concerning return and flexibility. Once the steady state can be calculated for given growth rates, the investment policy can be specified. The importance of taking account of a growth rate is illustrated. Growth in volume implies that a different rule will converge to the desired steady state. This is illustrated analytically and with numerical examples. The purpose of the paper is not to find the ideal hedge strategy for non-maturity liabilities, but to improve the existing risk management without any implementation costs for the banks. Given the currently used methodology, accounting for a growth rate can significantly improve the risk management of non-maturity liabilities. RID="*" ID="*" I thank Anja De Waegenaere, Peter Kort and an anonymous referee for useful comments on an earlier draft.     

A dispatching method for automated guided vehicles by using a bidding concept

A dispatching method is suggested for automated guided vehicles by using an auction algorithm. The dispatching method in this study is different from traditional dispatching rules in that it looks into the future for an efficient assignment of delivery tasks to vehicles and also in that multiple tasks are matched with multiple vehicles. The dispatching method in this study is distributed in the sense that the dispatching decisions are made through communication among related vehicles and machines. The theoretical rationale behind the distributed dispatching method is also discussed. Through a simulation study, the performance of the method is compared with that of a popular dispatching rule. RID="*" ID="*" The research was financially supported by the Sasakawa Scientific Research Grant from The Japan Science Society. The original version of the simulation program is provided by Professor Jae Yeon Kim at Dong Yang University, Korea. Correspondence to: J. K. Lim     

Portfolio Insurance and model uncertainty

Some real-world insurance products contain a minimum-wealth or an income-stream guarantee, both of which have to be met irrespective of capital market conditions. Therefore, sellers of such products are well advised to pursue a portfolio strategy that can meet these minimum investment goals if they want to avoid additional cash payments. Portfolio Insurance seems to be the solution to this portfolio problem. However, this paper shows that Portfolio Insurance cannot protect minimum investment goals because its strategies are fitted to a particular form of market risk. Decision makers do not know for sure (with probability one) what the true form of market risk is (model uncertainty); thus model uncertainty makes Portfolio Insurance fail. RID="*" ID="*" I thank two anonymous referees and the participants of the “3rd Passauer Finanzwerkstatt”, in particular Ariane Rei? and Thomas Braun, for their valuable comments. In addition, special thanks goes to Alexander Kempf, whose suggestions have significantly improved the paper.     

Intensity-modulated radiotherapy – a large scale multi-criteria programming problem

Abstract. Radiation therapy planning is often a tight rope walk between dangerous insufficient dose in the target volume and life threatening overdosing of organs at risk. Finding ideal balances between these inherently contradictory goals challenges dosimetrists and physicians in their daily practice. Todays inverse planning systems calculate treatment plans based on a single evaluation function that measures the quality of a radiation treatment plan. Unfortunately, such a one dimensional approach cannot satisfactorily map the different backgrounds of physicians and the patient dependent necessities. So, too often a time consuming iterative optimization process between evaluation of the dose distribution and redefinition of the evaluation function is needed. In this paper we propose a generic multi-criteria approach based on Pareto's solution concept. For each entity of interest – target volume or organ at risk – a structure dependent evaluation function is defined measuring deviations from ideal doses that are calculated from statistical functions. A reasonable bunch of clinically meaningful Pareto optimal solutions are stored in a data base, which can be interactively searched by physicians. The system guarantees dynamic planning as well as the discussion of tradeoffs between different entities. Mathematically, we model the inverse problem as a multi-criteria linear programming problem. Because of the large scale nature of the problem it is not possible to solve the problem in a 3D-setting without adaptive reduction by appropriate approximation schemes. Our approach is twofold: First, the discretization of the continuous problem results from an adaptive hierarchical clustering process which is used for a local refinement of constraints during the optimization procedure. Second, the set of Pareto optimal solutions is approximated by an adaptive grid of representatives that are found by a hybrid process of calculating extreme compromises and interpolation methods. Correspondence to: K.-H. Küfer     

Design Support Using Distributed Web-Based AI Tools

Currently, designers are faced with searching through a ‘sea’ of on-line knowledge to support their decision making activities. This paper describes WebCADET, which is a reimplementation of the stand-alone CADET – a Knowledge-Based System (KBS) for product design evaluation. WebCADET aims to provide effective and efficient support for designers during their searches for design knowledge. WebCADET uses the ‘AI as text’ approach, where KBSs can be seen as a medium to facilitate the communication of design knowledge between designers. The development of WebCADET to include practical support via World Wide Web-based functionality, which illustrates the potential of the ‘AI as text’ approach, is described in the paper.     

Fluid–structure interaction modeling of ringsail parachutes

In this paper, we focus on fluid–structure interaction (FSI) modeling of ringsail parachutes, where the geometric complexity created by the “rings” and “sails” used in the construction of the parachute canopy poses a significant computational challenge. It is expected that NASA will be using a cluster of three ringsail parachutes, referred to as the “mains”, during the terminal descent of the Orion space vehicle. Our FSI modeling of ringsail parachutes is based on the stabilized space–time FSI (SSTFSI) technique and the interface projection techniques that address the computational challenges posed by the geometric complexities of the fluid–structure interface. Two of these interface projection techniques are the FSI Geometric Smoothing Technique and the Homogenized Modeling of Geometric Porosity. We describe the details of how we use these two supplementary techniques in FSI modeling of ringsail parachutes. In the simulations we report here, we consider a single main parachute, carrying one third of the total weight of the space vehicle. We present results from FSI modeling of offloading, which includes as a special case dropping the heat shield, and drifting under the influence of side winds.     

Lot-sizing for a single-stage single-product production system with rework of perishable production defectives

We consider a single-stage single-product production system. Produced units may be non-defective, reworkable defective, or non-reworkable defective. The system switches between production and rework. After producing a fixed number (N) of units, all reworkable defective units are reworked. Reworkable defectives are perishable or can become technologically obsolete. We assume that the rework time and the rework cost increase linearly with the time that a unit is held in stock. Therefore, N should not be too large. On the other hand, N should not be too small either, since there are set-up times and costs associated with switching between production and rework. For a given N, we derive an explicit expression for the average profit (sales revenue minus costs). Using this expression, the optimal value for N can be determined numerically. Moreover, it is easy to perform a sensitivity analysis, as we illustrate. RID="*" ID="*"The research of Dr. Ruud H. Teunter has been made possible by a fellowship of the Royal Netherlands Academy of Arts and Sciences. The research presented in this paper is part of the research on re-use in the context of the EU sponsored TMR project REVersed LOGistics (ERB 4061 PL 97-5650) in which take part the Otto-von-Guericke Universitaet Magdeburg (D), the Erasmus University Rotterdam (NL), the Eindhoven University of Technology (NL), INSEAD (F), the Aristoteles University of Thessaloniki (GR), and the University of Piraeus (GR). We thank the anonymous referees for their many helpful comments. Correspondence to: R. H. Teunter     

Developing Strategic Alliances: A Framework for Collaborative Negotiation in Design

This work applies a theory-based framework of collaborative negotiation to some of the disputes that regularly arise during group design. Although the framework was developed to provide general support for group work, this paper focuses on its use as a design tool. The framework, embodied in our system NegotiationLens, has four facets. It: 1. Provides a negotiation method intended to produce gain for all parties. 2. Provides an efficient process for conflict resolution. 3. Develops working alliances. 4. Lets parties decide quickly when they should go their separate ways. The framework produces the above results by: • Helping parties develop well-reasoned and clearly articulated points of view (Adelson and Jordan, 1991; Conklin and Yakemovic, 1991; Conklin and Begeman, 1988; MacLean et al ., 1991). • Creating a context of committment and respect. • Moving negotiating parties away from an adversarial stance and into a collaboration. • Allowing joint construction of solutions that are more beneficial than the unilateral solutions each party initially brought to the table. We present our framework for collaborative negotiation, describe NegotiationLens, and present two cases in which it was used. We present a third case, a large design project with recurrent design conflicts, and argue how NegotiationLens could have been of benefit there.     

Scheduling vehicles in automated transportation systems Algorithms and case study

One of the major planning issues in large scale automated transportation systems is so-called empty vehicle management, the timely supply of vehicles to terminals in order to reduce cargo waiting times. Motivated by a Dutch pilot project on an underground cargo transportation system using Automated Guided Vehicles (AGVs), we developed several rules and algorithms for empty vehicle management, varying from trivial First-Come, First-Served (FCFS) via look-ahead rules to integral planning. For our application, we focus on attaining customer service levels in the presence of varying order priorities, taking into account resource capacities and the relation to other planning decisions, such as terminal management. We show how the various rules are embedded in a framework for logistics control of automated transportation networks. Using simulation, the planning options are evaluated on their performance in terms of customer service levels, AGV requirements and empty travel distances. Based on our experiments, we conclude that look-ahead rules have significant advantages above FCFS. A more advanced so-called serial scheduling method outperforms the look-ahead rules if the peak demand quickly moves amongst routes in the system. Received: June 21, 2000 / Accepted: January 22, 2001     

Meta-heuristic based decision support for portfolio optimization with a case study on tracking error minimization in passive portfolio management

In this paper we describe the concept and design of a meta-heuristic based decision support system generator (DSS-generator) for portfolio optimization. We report extensively on experience with the application of a specific DSS that has been customized for controlling and optimizing passively managed stock funds. Here, the constraints from the law on investment trust companies as well as several fund specific guidelines prohibit that the benchmark can be identically reproduced. For measuring the performance of the portfolio a tracking error model with data stemming from a factor model is applied. Our results show that the system provides proposals for the fund manager in acceptable time which are feasible with respect to the guidelines and excellent in quality.     

Estimating financial risk under time-varying extremal return behavior

Potentially increasing volatility and downside risk is essential to financial risk management which is concerned with the tails, or particularly, the lower tail, of the distribution of speculative asset returns. Applying extreme value theory, the present paper outlines a simple model capturing time-varying tail behavior and studies conditional daily return quantiles for the German DAX. Our results indicate an overall increased risk of large one-day holding-period losses related to a structural break given by the 1987 crash, systematic out-of-sample underestimation of the magnitude of extreme quantiles as well as clustering in estimated quantile exceedances which cannot be fully explained by the forecasting model. RID="*" ID="*" Part of the paper was written while the author was visiting the Center for Mathematical Sciences at Munich University of Technology. He is grateful for the members' hospitality and thanks Claudia Klüppelberg for helpful discussions as well as two anonymous referees for comments improving the paper.