A framework for decision support systems for scheduling problems

Considering a decision support system as a tool where executive's judgment can be included along with the mathematical tool kit of the management scientist, this paper shows the need to include problem management as an integral component of the decision support system for scheduling problems. A methodology based on the resolution of conflicts among various constraints in scheduling problems is proposed to implement the problem management system in a decision support system for these problems. The paper concludes with some guidelines to create a workable framework for providing effective decision support to solve scheduling problems and the identification of some fruitful directions for future research.     

Tentative guidelines to help choosing an appropriate MCDA method

Despite the development of a large number of refined multicriterion decision aid (MCDA) methods, none can be considered as the `super method' appropriate to all decision making situations. Hence, how can one choose an appropriate method to a specific decision situation? Recent experimental studies in psychology and behaviour have revealed, on the one hand, that the human thinking is not to be modelled by logical rules and calculations, and, on the other hand, that the response mode affects the preference formation as well as the use of compensatory or noncompensatory strategies. The aim of this paper is to draw a conceptual framework for articulating tentative guidelines to choose an appropriate MCDA method. This paper also presents the results of the comparison of well known multicriterion aggregation procedures (MCAP) on the basis of these guidelines. In our opinion this study can constitute a first step for proposing a methodological approach to select an appropriate MCDA method to a specific decision making situation. Such an approach should be validated and may be integrated into a decision support system. Moreover, the framework suggested is helpful to develop useful methods and to address neglected issues within the field.     

A web-based decision support system for waste lube oils collection and recycling

This paper presents a web-based decision support system (DSS) that enables schedulers to tackle reverse supply chain management problems interactively. The focus is on the efficient and effective management of waste lube oils collection and recycling operations. The emphasis is given on the systemic dimensions and modular architecture of the proposed DSS. The latter incorporates intra- and inter-city vehicle routing with real-life operational constraints using shortest path and sophisticated hybrid metaheuristic algorithms. It is also integrated with an Enterprise Resource Planning system allowing the utilization of particular functional modules and the combination with other peripheral planning tools. Furthermore, the proposed DSS provides a framework for on-line monitoring and reporting to all stages of the waste collection processes. The system is developed using a web architecture that enables sharing of information and algorithms among multiple sites, along with wireless telecommunication facilities. The application to an industrial environment showed improved productivity and competitiveness, indicating its applicability on realistic reverse logistical planning problems.     

A strategic decision support system framework for energy-efficient technology investments

Energy systems optimization under uncertainty is increasing in its importance due to on-going global de-regulation of the energy sector and the setting of environmental and efficiency targets which generate new multi-agent risks requiring a model-based stakeholders dialogue and new systemic regulations. This paper develops an integrated framework for decision support systems (DSS) for the optimal planning and operation of a building infrastructure under appearing systemic de-regulations and risks. The DSS relies on a new two-stage, dynamic stochastic optimization model with moving random time horizons bounded by stopping time moments. This allows to model impacts of potential extreme events and structural changes emerging from a stakeholders dialogue, which may occur at any moment of the decision making process. The stopping time moments induce endogenous risk aversion in strategic decisions in a form of dynamic VaR-type systemic risk measures dependent on the system’s structure. The DSS implementation via an algebraic modeling language (AML) provides an environment that enforces the necessary stakeholders dialogue for robust planning and operation of a building infrastructure. Such a framework allows the representation and solution of building infrastructure systems optimization problems, to be implemented at the building level to confront rising systemic economic and environmental global changes.     

Hit or miss: A decision support system framework for signing new musical talent

In the music industry, the process of signing new musical talent is one of the most complex decision-making problems. The decision, which is generally made by an artist and repertoire (A&R) team, involves consideration of various quantitative and qualitative criteria, and usually results in a low success rate. We conducted a series of mental model interviews with the aim of developing a decision support framework for A&R teams. This framework was validated by creating a decision support system that utilises multi-criteria decision analysis to support decision-making. Our framework and subsequent implementation of the decision support system involving decision rule and weighted sum methods show an improvement in the ability to analyse and decide on greater amounts of talent. This paper serves as a building block for developing systems to aid in this complex decision-making problem.     

An interactive desirability function method to multiresponse optimization

Multiresponse optimization problems often involve incommensurate and conflicting responses. To obtain a satisfactory compromise in such a case, a decision maker (DM)’s preference information on the tradeoffs among the responses should be incorporated into the problem. This paper proposes an interactive method based on the desirability function approach to facilitate the preference articulation process. The proposed method allows the DM to adjust any of the preference parameters, namely, the shape, bound, and target of a desirability function in a single, integrated framework. The proposed method would be highly effective in generating a compromise solution that is faithful to the DM’s preference structure.     

Real-time decision problems: an operational research perspective

This paper is concerned with a class of dynamic and stochastic problems known as real-time decision problems. The objective is to provide responses of a required quality in a continuously evolving environment, within a prescribed time frame, using limited resources and information that is often incomplete or uncertain. Furthermore, the outcome of any particular decision may also be uncertain. This paper provides an overview of this class of problems, reviews the relevant Artificial Intelligence literature, proposes a dynamic programming framework, and assesses the potential usefulness of Operational Research approaches for their solution. Throughout the paper, a vehicle dispatching application illustrates the relevant concepts.     

The sustainability balanced scorecard as a framework for selecting socially responsible investment: an effective MCDM model

In recent years, sustainable development and social responsibility have become important issues around the globe. Investors are interested in the so-called ‘socially responsible investment’ (SRI), an investment strategy that employs criteria other than financial risk and return when selecting firms in which to invest. The practice of SRI shows that there are growing numbers of investors who want to take account of more criteria. Given this worldwide trend, the question arises how these issues can be incorporated into the investment decision process. This paper proposes a novel integrated model for selecting SRI stocks and illustrates the practical application of such a model through a case study. This model first applied the decision making trial and evaluation laboratory (DEMATEL) approach to deal with the interdependencies existing among the criteria of organization requires, and then integrated the DEMATEL, the analytic network process, and the zero-one goal programming method to select an optimal portfolio of SRI. Additionally, we used the sustainability balanced scorecard as a multi-criteria framework for SRI evaluation. This integrated model enables the management to obtain the fitting SRI portfolio and achieves the desired spiritual value.     

Simulation-based framework to improve patient experience in an emergency department

The global economic crisis has a significant impact on healthcare resource provision worldwide. The management of limited healthcare resources is further challenged by the high level of uncertainty in demand, which can lead to unbalanced utilization of the available resources and a potential deterioration of patient satisfaction in terms of longer waiting times and perceived reduced quality of services. Therefore, healthcare managers require timely and accurate tools to optimize resource utility in a complex and ever-changing patient care process. An interactive simulation-based decision support framework is presented in this paper for healthcare process improvement. Complexity and different levels of variability within the process are incorporated into the process modeling phase, followed by developing a simulation model to examine the impact of potential alternatives. As a performance management tool, balanced scorecard (BSC) is incorporated within the framework to support continual and sustainable improvement by using strategic-linked performance measures and actions. These actions are evaluated by the simulation model developed, whilst the trade-off between objectives, though somewhat conflicting, is analysed by a preference model. The preference model is designed in an interactive and iterative process considering decision makers preferences regarding the selected key performance indicators (KPIs). A detailed implementation of the framework is demonstrated on an emergency department (ED) of an adult teaching hospital in north Dublin, Ireland. The results show that the unblocking of ED outflows by in-patient bed management is more effective than increasing only the ED physical capacity or the ED workforce.     

Computer-based models and the problem of investment in water resources: A case study

In this paper, a case study in regional water resources planning is presented in which the process of design and use of computer-based models and man-computer interaction is considered, especially with respect to the roles of designers and potential users. Key decisions in the design process are recognized and analyzed. It is concluded that integration of normative models in decision processes with conflicts shows limits that partly may be overcome by emphasis on the planning stage of the design process, and on development of planning and decision models that allow flexibility. Interactive procedures should be developed that distribute flexibility over decision levels and also deal with the problems of asymmetrical distributed information. It is concluded further that there is a need for a more systematical investigation of design processes and decision behavior related to characteristics of decision problems and environments.     

A framework for performance measurement during production ramp-up of assembly stations

Production ramp-up is an important phase in the lifecycle of a manufacturing system which still has significant potential for improvement and thereby reducing the time-to-market of new and updated products. Production systems today are mostly one-of-a-kind complex, engineered-to-order systems. Their ramp-up is a complex order of physical and logical adjustments which are characterised by try and error decision making resulting in frequent reiterations and unnecessary repetitions. Studies have shown that clear goal setting and feedback can significantly improve the effectiveness of decision-making in predominantly human decision processes such as ramp-up. However, few measurement-driven decision aides have been reported which focus on ramp-up improvement and no systematic approach for ramp-up time reduction has yet been defined. In this paper, a framework for measuring the performance during ramp-up is proposed in order to support decision making by providing clear metrics based on the measurable and observable status of the technical system. This work proposes a systematic framework for data preparation, ramp-up formalisation, and performance measurement. A model for defining the ramp-up state of a system has been developed in order to formalise and capture its condition. Functionality, quality and performance based metrics have been identified to formalise a clear ramp-up index as a measurement to guide and support the human decision making. For the validation of the proposed framework, two ramp-up processes of an assembly station were emulated and their comparison was used to evaluate this work.     

Modelling and decision support in physiology and medicine: a methodological framework with lllustration

This paper presents a methodological framework for modelling that has found wide application in the complex domains of physiology and medicine. The processes of model validation are centrally embedded within this framework. The parallelism between modelling per se and the development of model-based decision support systems is then considered, showing that it is possible to devise a unified methodological framework which encompasses the requirements both of model validation and decision support system evaluation. The applicability of the framework is demonstrated in the validation of a mathematical model of blood glucose dynamics; and in the development and evaluation of decision support systems such as those which are aimed at addressing the problem of advising the insulin-dependent diabetic patient on the adjustment of insulin dosage     

Planning and scheduling of selective harvest with management zones delineation

This paper considers an integrated approach to two common problems in a precision agriculture framework: management zone delineation and selective harvest scheduling. Our model minimizes the total costs of harvest operations, establishing planning and scheduling for selective harvest of each selected management zone. Therefore, this tool provides important information for decision making of farmers in the field. Our integrated model is contrasted with the hierarchical approach commonly used in the literature for these cases, where the result of zoning problem is an input to schedule the harvest problem. Both problems were solved through a complete enumeration of all the potential management zones and demonstrated the advantages of our proposed model over the hierarchical approach. Our model reached an average reduction of 10% in harvest operations costs for different instances in a case study.

     

A Decision Support System for Crew Planning in Passenger Transportation Using a Flexible Branch-and-Price Algorithm

This paper discusses a decision support system for airline and railway crew planning. The system is a state-of-the-art branch-and-price solver that is used for crew scheduling and crew rostering. Since it is far from trivial to build such a system from the information provided in the existing literature, technical issues about the system and its implementation are covered in more detail. We also discuss several applications. In particular, we focus on a specific aircrew rostering application. The computational results contain an interesting comparison of results obtained with the approach in which crew scheduling is carried out before crew rostering, and an approach in which these two planning problems are solved in an integrated manner.     

A multiattribute GDSS for aiding problem-solving

This study proposes a group decision support system (GDSS) with multiattribute to help solve problems in the real world. The problems are usually characterized as a multiattribute decision making (MADM) for selections, and shall be the responsibility of an expert group. On a regular basis, experts within that group will meet and conduct discussions on the web. After each individual make efforts of judgments, comparisons, and rankings, they shall determine, collectively as a group, the final rankings of all possible alternatives. Furthermore, aimed at insuring the decision quality of the collective decisions, an integrated procedure will be applied to make any modifications as necessary. Based on the geometric aspects of decision quality, the disparity of each individual member's preferences on attribute can be filtered out by the suggested bounded indicators. And then the outliers related to attributes' weights will be identified through a different set of consensus indicators, thus, further improving the decision quality while maintaining a quantitative level of consensus. Finally, using a car-selection problem herein, the proposed integrated procedure is implemented on a network-based PC system with web interfaces.     

Balancing efficiency and equity in location-allocation models with an application to strategic EMS design

This paper presents an integrated location-allocation model balancing efficiency and equity criteria. The new formulation combines two domains: facility location and data envelopment analysis. To support the decision maker with more realistic solutions based on the optimal location-allocation decisions, we endogenize the outputs of the model as a function dependent on the allocation variables. To illustrate the viability of the proposed approach, we investigated the potential application of the model to the design of an emergency medical service system.     

Design of an IT-driven decision support system for vehicle routing and scheduling

This paper presents the development of a decision support system used by an oil downstream company for routing and scheduling purposes. The studied problem refers to a complex delivery process of oil products from a number of distribution centers to all customers. The latest rapid advance of operations research (OR) applications, in the form of advanced planning and scheduling (APS) systems, has shown that OR algorithms can be applied in practice if (a) they are embodied in packaged information technology (IT) solutions, (b) the interface problems to mainstream ERP software applications are solved. In this study the utilisation of advanced IT systems supports effectively the planning and management of distribution operations. The combination of a supply chain management (SCM) application with a geographical information system (GIS) integrated with an enterprise resource planning (ERP) software resulted to this innovative decision support tool. The objectives of this new tool are: optimum use of the distribution network resources, transportation cost reduction and customer service improvement. The paper concludes with the benefits of the new system, emphasising at how new technologies can support transportation processes with the help of operations research algorithms embedded in software applications.     

Interactive multicriteria procedure exploiting a knowledge-based module to select electricity production alternatives: The CASTART system

For some decisional problems, it is difficult to have a set of potential alternatives a priori. This is true, for instance, when the object of the decision is dependent on an external environment, as in the case of disturbance situations in industrial processes. Computer assistance must support, first, the elaboration of a potential alternatives set and, second, the decision-making activity which will determine the decision elements leading to recovery from the disturbance. This paper deals with such a situation encountered in an electricity production context. An interactive multicriteria procedure exploiting a knowledge-based module to select electricity production alternatives is presented. Section 1 introduces the electricity production-consumption framework and identifies the Spinning Reserve Mobilization (SRM) function. Next, our contribution to the systematization and the experimentation of a decision-making process which supports the dispatcher confronted with an SRM situation is described. The decision-making process includes an intelligent module and a decisional procedure. The module and the procedure, and their interconnections, are developed in Section 2. Section 3 describes the DSS called CASTART which implements this process. An overview of DSS functionalities is given, as well as the results obtained by a dispatcher working in cooperation with the system, in the case of a simulated production incident.     

Concurrent optimization in designing for logistics support

Concurrent Engineering has always been an important field within military industry and is gaining recognition within commercial industry as well. Studies have suggested that long-range research efforts need to be directed to the area of integrated logistics. In order to satisfy the overall logistics objectives, product designs must incorporate consideration of the impact that design decisions have on operations, maintenance, transportation and supply. This paper presents a model that carries out a concurrent optimization of a product design and its associated manufacturing and logistics support systems. We offer this model as a framework for decision support of concurrent engineering activities.     

Some issues in mathematical modelling of multiple criteria decision-making problems

Models for analyzing and solving multiple criteria decision-making (MCDM) problems are difficult to evaluate and compare, because they are intended for diverse orderings of a set of feasible alternatives. These models are based on a variety of assumptions about the decision maker's preferences and use different types of preference information. In this paper, a conceptual framework is developed for evaluating and comparing discrete alternative MCDM models available for a given decision situation. The procedure employed in the framework guides the user through an analysis of the decision situation making it possible for a decision maker or analyst to select the most appropriate MCDM model from among several alternative feasible models.