Modelling empty vehicle traffic in AGVS design

Empty vehicle traffic plays a critical role in the operating performance of automated guided vehicle systems (AGVSs). While significant research has been conducted on intelligent AGVS dispatching-which, in essence, is the management of empty vehicle traffic-research in AGVS design has sometimes ignored or simplified the role of empty vehicle traffic. In this paper, we show how empty vehicle traffic strongly influences several important AGVS design problems, such as flowpath design and vehicle requirements. We present analytical models to predict empty vehicle travel under two popular vehicle dispatching rules for systems facing stochastic trip demand. We show that using our models' estimates of empty vehicle traffic in the AGVS design process can dramatically improve the resulting system performance. We also analyse shop-floor transfer patters and find that empty traffic has a larger impact on systems with discernible trends in job movement.     

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     

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.     

On extreme values of orbit lengths in M/G/1 queues with constant retrial rate

In the design of waiting facilities for the units in a retrial queue, it is of interest to know probability distributions of extreme values of the orbit length. The purpose of this paper is to investigate the asymptotic behavior of the maximum orbit length in the queue with constant retrial rate, as the time interval increases. From the classical extreme value theory, we observe that, under standard linear normalizations, the maximum orbit length up to the nth time the positive recurrent queue becomes empty does not have a limit distribution. However, by allowing the parameters to vary with n, we prove the convergence of maximum orbit lengths to three possible limit distributions when the traffic intensity approaches 1 from below and n approaches infinity.

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Received: October 7, 1999 / Accepted: November 21, 2000     

Modeling and optimization of the intermodal terminal Mega Hub

The convergence of European states can be expected to lead to an increase in the trading of goods within the next few years and thus to a growing demand for transport. Overland intermodal transport is an important development, because it combines the advantages of rail for long distance transportation with the effective area cover offered by road. Different terminal concepts and production forms have been developed to increase the flexibility of intermodal transport and to make it more attractive for the customer. The intermodal terminal concept investigated in this paper is called Mega Hub. The configuration and the control of the terminal is a complex and challenging task. Here, the terminal is modeled as a multi-stage transshipment problem. In this approach, sequence-dependent duration of empty moves, alternative assignments (of containers to cranes) and a sequence-dependent number of operations have to be handled. An optimization model based on Constraint Satisfaction is formulated and heuristics for the search procedure, especially value and variable ordering are developed. Received: May 2, 2000 / Accepted: July 4, 2001     

Models and algorithms for solving combined vehicle and crew scheduling problems with rest constraints : an application to road feeder service planning in air cargo transportation

We present a mathematical model and two algorithms for solving a complex combined vehicle and crew scheduling problem. The problem arises in the area of road feeder service (RFS) for air cargo transportation where cargo airlines engage specifically equipped RFS-carriers to serve so-called lines, i.e. regular weekly patterns of trips starting and ending at the central hub, respectively. The complexity of the problem stems from the time windows, the rest regulations for drivers and the highly heterogenous requirements with respect to the fleet. The model can be applied to different planning scenarios at the RFS-carrier as well as the airline. The model and method has been incorporated into a decision support system called block.buster where sequences of single trips are combined to feasible blocks starting and ending at the hub and then combined to feasible vehicle round trips.     

Combined strategic and operational planning – an MILP success story in chemical industry

We describe and solve a real world problem in chemical industry which combines operational planning with strategic aspects. In our simultaneous strategic & operational planning (SSDOP) approach we develop a model based on mixed-integer linear (MILP) optimization and apply it to a real-world problem; the approach seems to be applicable in many other situations provided that people in production planning, process development, strategic and financial planning departments cooperate. The problem is related to the supply chain management of a multi-site production network in which production units are subject to purchase, opening or shut-down decisions leading to an MILP model based on a time-indexed formulation. Besides the framework of the SSDOP approach and consistent net present value calculations, this model includes two additional special and original features: a detailed nonlinear price structure for the raw material purchase model, and a detailed discussion of transport times with respect to the time discretization scheme involving a probability concept. In a maximizing net profit scenario the client reports cost saving of several millions US$. The strategic feature present in the model is analyzed in a consistent framework based on the operational planning model, and vice versa. The demand driven operational planning part links consistently to and influences the strategic. Since the results (strategic desicions or designs) have consequences for many years, and depend on demand forecast, raw material availability, and expected costs or sales prices, resp., a careful sensitivity analysis is necessary showing how stable the decisions might be wit h respect to these input data.     

Coordination Approaches and Systems – Part II: An Operational Perspective

This is the second of two papers surveying research in coordination approaches and systems. This paper is concerned with operational coordination, which is aimed at coordinating activities such that the design process can be performed in a near optimal manner with respect to time, and the allocation and utilisation of resources. Aspects of coordination categorised as operational include resource management, scheduling and planning. The first of these two papers presents a review of coordination from a strategic perspective, which is concerned with the decision management aspects of coordination. Greater emphasis is now being placed on the significance of organising the design process as this affects time to market, product quality, cost, and consequently product success. The aim of this paper is to present a fundamental review of operational coordination approaches and systems. The 1990s has seen much progress being made towards a greater understanding and appreciation of coordination in various disciplines through the development of a wide range of approaches and systems. However, there remains a requirement to formally identify the key issues involved in coordination such that a widely accepted representation can be agreed upon. Consequently, research should continue to be supported in the exploration for a unified approach to coordination which will permit a broader and greater understanding of those aspects involved.     

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     

考虑客户满意度的车辆路径优化研究

针对传统的车辆路径问题较少关注客户满意度的情况，以客户对服务时间和货物完好性的要求来衡量客户满意度，构建基于模糊时间窗的时间满意度函数和基于货损率的货物完好满意度函数，在此基础上以客户满意度最大和运输成本最小为目标建立优化模型，设计相应算例并利用LINGO17.0软件进行求解，与中小物流企业常用的扫描法进行对比验证模型的有效性。结果表明：利用LINGO17.0求得的优化结果与扫描法相比，虽然运输成本有一定增加，但相应的平均客户满意度提高了36.3%，建立的模型能较好地平衡客户满意度和运输成本，对于物流企业配送路径的决策优化有一定的参考价值。     

Functional Interdependence and Product Similarity Based on Customer Needs

In this paper, related product functions are determined for a group of approximately 70 consumer products. Using customer need data, a new matrix approach is introduced to identify these relationships. Techniques are then created for determining product similarity. These techniques are clarified and validated through three case studies, including beverage brewers and material-removal products. The results of these case studies are argued to have significant impact on design-by-analogy procedures, benchmarking methods, mass customization strategies and modular design. The paper concludes with a discussion of applications and related procedures for product development.     

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     

Makespan estimation and order acceptance in batch process industries when processing times are uncertain

Batch process industries are characterized by complex precedence relationships between operations, which renders the estimation of an acceptable workload very difficult. A detailed schedule based model can be used for this purpose, but for large problems this may require a prohibitive large amount of computation time. We propose a regression based model to estimate the makespan of a set of jobs. We extend earlier work based on deterministic processing times by considering Erlang-distributed processing times in our model. This regression-based model is used to support customer order acceptance. Three order acceptance policies are compared by means of simulation experiments: a scheduling policy, a workload policy and a regression policy. The results indicate that the performance of the regression policy can compete with the performance of the scheduling policy in situations with high variety in the job mix and high uncertainty in the processing times. Correspondence to: C.V. Ivanescu     

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.     

A-Design: An Agent-Based Approach to Conceptual Design in a Dynamic Environment

This paper provides an introduction to a new design methodology known as A-Design, which combines aspects of multi-objective optimization, multi-agent systems, and automated design synthesis. The A-Design theory is founded on the notion that engineering design occurs in interaction with an ever-changing environment, and therefore computer tools developed to aid in the design process should be adaptive to these changes. In this paper, A-Design is introduced along with some simple test problems to demonstrate the capabilities of different aspects of the theory. The theory of A-Design is then shown as the basis for a design tool that adaptively creates electro-mechanical configuration designs for changing user preferences.     

Designing Assemblies

This paper presents a theory to support the design of assemblies. It brings together prior work in a new synthesis, resulting in a top-down process for designing assemblies so that they deliver geometric Key Characteristics (KCs) that achieve top level customer requirements. The theory applies to assemblies that take the form of mechanisms (e.g. engines) or structures (e.g. aircraft fuselages), but has less relevance to assemblies that take the form of connective or distributive systems (e.g. hydraulic piping). The theory shows how kinematically constrained (statically determinate) assemblies can be unambiguously designed to satisfy geometrically-defined customer requirements. The top-down process presented here begins by creating a kinematic constraint structure and a systematic scheme by which parts are located in space relative to each other, followed by declaration of assembly features that join parts in such a way as to create the desired constraint relationships. This process captures design intent by creating a connective data model that contains information to support relevant analyses such as variation buildup, constraint analysis, and establishment of constraint-consistent assembly sequences. Adjustable assemblies, assemblies built using fixtures, and selective assemblies can also be described by this theory. Problems arising from multiple KCs and KC conflict can be identified. Issues unresolved by the theory are also noted.     

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.     

Performance analysis of parallel identical machines with a generalized shortest queue arrival mechanism

In this paper we study a production system consisting of a group of parallel machines producing multiple job types. Each machine has its own queue and it can process a restricted set of job types only. On arrival a job joins the shortest queue among all queues capable of serving that job. Under the assumption of Poisson arrivals and identical exponential processing times we derive upper and lower bounds for the mean waiting time. These bounds are obtained from so-called flexible bound models, and they provide a powerful tool to efficiently determine the mean waiting time. The bounds are used to study how the mean waiting time depends on the amount of overlap (i.e. common job types) between the machines.

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Received: February 8, 2000 / Accepted: November 28, 2000     

Building Agility for Developing Agile Design Information Systems

Agile manufacturing relies heavily on the quality of information that organizations have and on their ability to organize and reuse it. Constant inflow of information and knowledge is the fuel of agile manufacturing. In the process of forming virtual enterprises, these new organizations have to be equipped with information systems that integrate their present legacy technology and improve upon it. To support the quick formation of virtual organizations, one must have the ability to develop such systems quickly. Over the past few years we have evolved, through collaborative projects with industry, an approach composed of methods and an information infrastructure called n-dim that improves the ability of becoming agile manufacturers of information systems, by responding quickly to information needs of new and evolving organizations. Following an analysis of the requirements of information systems for agile design, we discuss this approach; describe some of the infrastructure features; and present several examples of simple applications that illustrate them. We summarize by discussing the advantages and limitations of our approach.     

An application of mixed-integer linear programming models on the redesign of the supply network of Nutricia Dairy &; Drinks Group in Hungary

Between 1995 and 1998 Nutricia acquired a number of dairy companies in Hungary. Each of these companies produced a wide variety of products for its regional market. Although alterations had been made to the production system in the last few years, production and transportation costs were still substantial. This paper presents a research study with regard to the optimisation of the supply network of Nutricia Hungary using a mixed-integer linear programming model. Focussing on consolidation and product specialisation of plants the objective was to find the optimal number of plants, their locations and the allocation of the product portfolio to these plants, when minimizing the sum of production and transportation costs. The model is in line with traditional location/allocation models, with a modification concerning inter-transportation of semi-finished products between plants. The production costs used in this model are based on a Green field situation, taking into account new and more advanced technologies available today. The model is used by the Nutricia Dairy and Drinks Group as a decision supporting tool. Correspondence to: F. H. E. Wouda