Resource allocation for HIV/AIDS control programs: a model-based policy analysis

The World Health Organization reported that in 1996, for the first time in the course of the AIDS epidemic, there had been a marked decrease in deaths among people with AIDS in many industrialized countries due to the administration of advanced drug therapies and the performance of prevention programs. In response to such changes, policy makers can use our strategic decision support system to determine cost-effective prevention programs. We illustrate the model by analyzing the administration of advanced drug therapies combined with different assumptions for the behavior of the population of Vienna. We estimate that the city of Vienna will have to provide at most 5.6 billion Austrian Schillings for drug therapies, additional treatment, and HIV screening during the period from 1996 to 2005, depending on whether or not these more costly drug therapies reduce the additional treatment costs of HIV-infected and AIDS-diseased individuals. Received: June 12, 2000 / Accepted: August 31, 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.     

A multi-agent system for chemical supply chain simulation and management support

Modern chemical production is customer-driven and the desired delivery time for the products is often shorter than their campaign length. In addition, the raw materials supplying time is often long. These features make it desirable to provide tools to support collaborative supply chain decision making, preferably over the Internet, and where there are conflicts, compromise decisions can be quickly reached and the effects of the decisions can be quantitatively simulated. This paper des cribes such a multi-agent system (MAS) that can be used to simulate the dynamic behaviour and support the management of chemical supply chains over the Internet. Geographically distributed retailers, logistics, warehouses, plants and raw material suppliers are modelled as an open and re-configurable network of co-operative agents, each performing one or more supply chain functions. Communication between agents is made through the common agent communication language KQML (knowledge query message language). A t the simulation layer, the MAS allows distributed simulation of the chain behaviour dynamically, so that compromise decisions can be rapidly and quantitatively evaluated. Because in a chemical supply chain the scheduling of the plant often dominates the chain performance, an optimum scheduling system for batch plants is integrated into the MAS. The functions of the system are illustrated by reference to a case study for the supply and manufacture using a multi-purpose batch plant of paints and coatings.     

A Dominance-based Design Metric in Multiattribute Robust Design

This paper outlines the development of an effective and consistent ‘designing-in-quality’ strategy that can be used to deal with concepts of uncertainty, quality and robustness in engineering design. Specifically, this paper presents a decision analysis-based robust design metric that seamlessly integrates objective evaluations on the goodness of a design alternative with the designer’s intent and preferences. This is achieved through the development of a set of performance-reflecting dominance indices for the attributes and their utilization in a preference-influenced multiattribute utility formulation. Such a knowledge feedback-based decision model development will be particularly useful when dealing with complex iteration-based engineering design process where little information on the expected outcomes may be known a priori, or where product performance is computationally expensive to evaluate. Application of this robust design metric in a multi-stage experimentation and modeling design process is presented. The characteristics of the proposed design metric and the effectiveness of the overall design procedure in dealing with constrained engineering design problems are examined with the aid of demonstrative case studies and the results are discussed.     

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.     

Framework for Modeling Dependencies in Collaborative Engineering Processes

This article describes an engineering process representation and modeling tool. The approach is especially suitable for describing large-scale, mature design processes involving numerous tasks, some of which may be performed by automated computer agents. The underlying representation is a graph of information-processing units with explicitly defined input and output feature elements. We show that this representation is more complete than those used in previous process modeling approaches and overcomes some of their limitations when dealing with design processes involving dependencies at multiple levels of detail. The representation is combined with rules for automatically operating upon the graph to preserve consistency when traversing to higher or lower levels of detail.     

Strategic technology planning in hospital management

Abstract. Hospital managers regularly are confronted with their patients' demand for increased service performance on the one hand and tight budgets on the other. As medical technologies influence both the costs and the service spectrum, strategic technology planning is among the critical tasks in hospital management. This paper addresses the corresponding problem of selecting the “best” portfolio of medical devices and proposes an appropriate decision support system. It starts with a multiobjective mathematical programming model that determines the solution space of all efficient portfolios of medical technology investments. The members of the planning committee with their diverging interests then are supported by their interactive exploration of that space until they jointly reach a satisfying portfolio and are not willing to make any further compromises between its objective levels. As one of its salient features the system does not require a priori preference information. RID="*" ID="*" A previous version of this paper has been presented at the Wiesbaden 2000 Meeting of the GOR-Working Group “Operations Research in Health Care”. The authors thank Andrea Lührs and Thomas Rollins, both from Siemens AG, for their valuable support. Moreover, thanks are due to the anonymous referees for their comments on a previous version of this paper. Correspondence to: C. Stummer     

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.     

Performing Changes in Product Development: A Framework with Keys for Industrial Application

Industrial product development requires continuous improvements in work procedures as a result of constantly changing demands. Support tools have proven to be an oft chosen way to meet new demands; however, few research efforts have been made in how to implement new tools. This article is a contribution to knowledge on carrying out the implementation of support tools. The basis consists of four field studies performed during 1994–1999, containing 78 qualitative research interviews and focusing on the implementation and use of different support tools. A re-analysis has been performed of selected interviews from the field studies, in total 30 interviews. This resulted in recommendations for an implementation framework, consisting of an Implementation Cycle, Organizational Change Field and Managerial Consistence, and five implementation keys: Goal setting, Kowledge Development, Anchoring at All Levels, Suitable Resources and Focus on the Individual.     

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.     

On the location of antennas for treatment planning in hyperthermia

Abstract. In this paper we investigate how to determine optimal locations of the microwave antennas being circularly ordered in a hyperthermia device. The heated area containing the tumor should have minimal volume. Based on a simple geometric model for the two and three dimensional case we develop algorithms for the computation of these volumes and present numerical results for the optimal locations. Correspondence to: J. Jahn     

Campaign planning for multi-stage batch processes in the chemical industry

Inspired by a case study from industry, the production of special chemical products is considered. In this industrial environment, multi-purpose equipment is operated in batch mode to carry out the diverse processing tasks. Often, extensive set-up and cleaning of the equipment are required when production switches between different types of products. Hence, processes are scheduled in campaign mode, i.e. a number of batches of the same type are processed in sequence. The production of chem ical products usually involves various stages with significant cumulative lead times. Typically, these production stages are assigned to different plants. A hierarchical modelling approach is presented which co-ordinates the various plant operations within the entire supply network. In the first stage, the length of the campaigns, their timing, the corresponding material flows, and equipment requirements have to be determined. At this stage, an aggregation scheme based on feasibility constraints is employed in order to reflect the limited availability of the various types of production equipment. The second stage consists of an assignment model, which allocates the available equipment units between the production campaigns determined in the first stage of the solution procedure. In the third stage, resource conflicts are resolved, which may occur if clean-out operations and minimal campaign lengths have to be considered. The proposed hierarchical approach allows a more compact model formulation compared to ot her approaches known from the literature. As a result, a very efficient and flexible solution approach is obtained. In particular, commercially available standard solvers can be used to solve a wide range of campaign planning problems arising in the chemical industry.     

Advanced production scheduling for batch plants in process industries

An Advanced Planning System (APS) offers support at all planning levels along the supply chain while observing limited resources. We consider an APS for process industries (e.g. chemical and pharmaceutical industries) consisting of the modules network design (for long–term decisions), supply network planning (for medium–term decisions), and detailed production scheduling (for short–term decisions). For each module, we outline the decision problem, discuss the specifi cs of process industries, and review state–of–the–art solution approaches. For the module detailed production scheduling, a new solution approach is proposed in the case of batch production, which can solve much larger practical problems than the methods known thus far. The new approach decomposes detailed production scheduling for batch production into batching and batch scheduling. The batching problem converts the primary requirements for products into individual batches, where the work load is to be minimized. We formulate the batching problem as a nonlinear mixed–integer program and transform it into a linear mixed–binary program of moderate size, which can be solved by standard software. The batch scheduling problem allocates the batches to scarce resources such as processing units, workers, and intermediate storage facilities, where some regular objective function like the makespan is to be minimized. The batch scheduling problem is modelled as a resource–constrained project scheduling problem, which can be solved by an efficient truncated branch–and–bound algorithm developed recently. The performance of the new solution procedures for batching and batch scheduling is demonstrated by solving several instances of a case study from process industries.