Mid-term and short-term planning support for home health care services

In this paper we are looking at routing and scheduling problems arising in the context of home health care services. Many small companies are working in this sector in Germany and planning is still done manually, resulting in long planning times and relatively inflexible solutions.     

A patient assignment algorithm for home care services

We consider the problem of assigning patients to nurses for home care services. The aim is to balance the workload of the nurses while avoiding long travels to visit the patients. We analyse the case of the CSSS Côte-des-Neiges, Métro and Parc Extension for which a previous analysis has shown that demand fluctuations may create work overload for the nursing staff. We propose a mixed integer programming model with some non-linear constraints and a non-linear objective which we solve using a Tabu Search algorithm. A simplification of the workload measure leads to a linear mixed integer program which we optimize using CPLEX.     

A matheuristic algorithm for stochastic home health care planning

Efficient human resource planning is the cornerstone of designing an effective home health care system. Human resource planning in home health care system consists of decisions on districting/zoning, staff dimensioning, resource assignment, scheduling, and routing. In this study, a two-stage stochastic mixed integer model is proposed that considers these decisions simultaneously. In the planning phase of a home health care system, the main uncertain parameters are travel and service times. Hence, the proposed model takes into account the uncertainty in travel and service times. Districting and staff dimensioning are defined as the first stage decisions, and assignment, scheduling, and routing are considered as the second stage decisions. A novel algorithm is developed for solving the proposed model. The algorithm consists of four phases and relies on a matheuristic-based method that calls on various mixed integer models. In addition, an algorithm based on the progressive hedging and Frank and Wolf algorithms is developed to reduce the computational time of the second phase of the proposed matheuristic algorithm. The efficiency and accuracy of the proposed algorithm are tested through several numerical experiments. The results prove the ability of the algorithm to solve large instances.     

A matheuristic approach for solving a home health care problem

We deal with a Home Health Care Problem (HHCP) which objective consists in constructing the optimal routes and rosters for the health care staffs. The challenge lies in combining aspects of vehicle routing and staff rostering which are two well known hard combinatorial optimization problems. To solve this problem, we initially propose an integer linear programming formulation (ILP) and we tested this model on small instances. To deal with larger instances we develop a matheuristic based on the decomposition of the ILP formulation into two problems. The first one is a set partitioning like problem and it represents the rostering part. The second problem consists in the routing part. This latter is equivalent to a Multi-depot Traveling Salesman Problem with Time Windows (MTSPTW).     

Wisdom,decision support and paradigms of decision making

Many decision support tools have been developed over the last 20 years and, in general, they support what Simon termed substantive rationality. However, such tools are rarely suited to helping people tackle wicked problems, for which a form of procedural rationality is better suited. Procedurally rational approaches have appeared in both management science and computer science, examples being the soft OR approach of cognitive mapping and the design rationale based on IBIS. These approaches are reviewed and the development of Wisdom, a procedurally rational decision support process and accompanying tool, is discussed and evaluated.     

The relationship between decision support systems and operational research: Health care examples

This paper explores, via selected case studies, the relationship between DSS and OR in the health field. Although I believe that DSS offers nothing really new, as described by various writers the term does emphasise particular features which should be desirable goals in any OR study. These features are: an emphasis on flexibility and adaptability, on ease of use and understanding by non-computer people and on models linked with traditional data access. The paper discusses such features and their desirability, in relation to hospital based planning/management on the one hand and community based planning on the other.     

Capturing preferences for inequality aversion in decision support

We investigate the situation where there is interest in ranking distributions (of income, of wealth, of health, of service levels) across a population, in which individuals are considered preferentially indistinguishable and where there is some limited information about social preferences. We use a natural dominance relation, generalised Lorenz dominance, used in welfare comparisons in economic theory. In some settings there may be additional information about preferences (for example, if there is policy statement that one distribution is preferred to another) and any dominance relation should respect such preferences. However, characterising this sort of conditional dominance relation (specifically, dominance with respect to the set of all symmetric increasing quasiconcave functions in line with given preference information) turns out to be computationally challenging. This challenge comes about because, through the assumption of symmetry, any one preference statement (“I prefer giving $100 to Jane and $110 to John over giving $150 to Jane and $90 to John”) implies a large number of other preference statements (“I prefer giving $110 to Jane and $100 to John over giving $150 to Jane and $90 to John”; “I prefer giving $100 to Jane and $110 to John over giving $90 to Jane and $150 to John”). We present theoretical results that help deal with these challenges and present tractable linear programming formulations for testing whether dominance holds between any given pair of distributions. We also propose an interactive decision support procedure for ranking a given set of distributions and demonstrate its performance through computational testing.     

Organizational decision support systems: Centralized support for decentralized organizations

Organizations are becoming increasingly decentralized in their operations and decision making. Advanced information technologies provide the glue that holds such organizations together and facilitates their operations. Organizational decision support systems (ODSSs) provide mechanisms for ensuring that the decisions being made throughout such organizations are consistent with each other and with the overall organization goals. Through means of an ODSS, information and guidance is automatically passed from higher levels to lower levels for use in decision-making models.     

Data analysis and decision support

In this paper, we consider developmental lines of computer-assisted decision support (with consideration of knowledge-based approaches) for data analysis problems. First, we discuss some situations where it is obviously appropriate to apply computer-assisted decision support in connection with data analysis tasks. Then, a brief historical retrospect is given viewing the development of this area of research and its interfaces to knowledge-based approaches. Against this background we illustrate two prototypes of knowledge-based decision support systems for specific data-analysis problems related to fields of interest of our own. Finally, we indicate possible progress and future activities in this area.     

Computerized support systems for emergency decision making

In all fields of human society, occasional emergencies are almost inevitable. Once an emergency occurs, rapid and proper decision making is required. The purpose of this paper is to explore the design and development of computerized support systems for emergency decision making (EDM). First the characteristics of EDM problems are examined. Then, in view of limited human computer rationality, requirements for a computerized support system for EDM are determined. A conceptual structure for knowledge-based distributed emergency decision support systems is proposed. Finally, a prototype system for safety protection and disaster response in coal mines, developed using the proposed structure, is briefly described.This work is partly supported by the State Science and Technology Commission of China, the National Key Laboratory on Industrial Control of China and Fok Ying Tung Education Foundation.     

Clinical decision support system for dental treatment

BackgroundIn this research, a decision making system, based on fuzzy inference mechanism as proposed by Mamdani, is presented. Literature suggests that there is a lack of consistency among dentists in choosing treatment plan(s). So, this research work aims to facilitate the dentist decide the treatment plan(s) of the broken tooth.MethodsAn expert system based on fuzzy logic has been designed to accept inaccurate and vague values of dental signs and symptoms associated with the broken tooth. We designed a knowledge base with 60 rules and used Mamdani inference algorithm to decide the possible one or more treatment(s) and suggest the same to the dentist.ResultsThe results proposed by the system are compared with the dentists’ suggestions. The Chi-square test of homogeneity is conducted on 100 randomly generated sample cases with the help of three professional dentists. It is found that the results produced by the system are consistent with the treatment plan(s) proposed by the dentists. Chi-square value of the test is 3.843565 which is less than the critical value which is 12.592. Hence, we are unable to reject the null hypothesis that assumes the two populations are homogeneous with respect to treatments.ConclusionsThe accuracy of the proposed decision support system for the treatment of broken tooth enhances the confidence level of the dentists while making decision regarding the treatment plan(s). Simple and interactive GUI makes it easy to use.     

Integrated decision support for aviation safety inspectors

This paper presents a systems viewpoint for developing an advanced decision support system for aircraft safety inspectors. Research results from a Federal Aviation Administration (FAA) sponsored project to use neural network and expert systems technology to analyze aircraft maintenance databases are summarized. One of the main objectives of this research is to define more refined “alert” indicators for national comparison purposes that can signal potential problem areas by aircraft type for safety inspector consideration.

Integration aspects are addressed on two levels: (1) integration of the various technical components of the decision support system, and (2) integration of the decision support system with individual behavior, management systems and organizational structure, as well as corporate culture across both formal and informal dimensions. The paper summarizes the creation of strategic “inspection profiles” for aging aircraft and reliability curve fitting for structural components both based upon using neural network technology. Also, the potential use of a model-based expert system to facilitate field inspection diagnostics is presented. Finally, a framework for developing an intelligent decision system to support aircraft safety inspections is proposed that links expert systems, neural networks, as well as a paradigm of the decision making process typically used in unstructured situations.     

A decision support system for wine-making cooperatives

A decision support system has been designed for viticultural cooperatives immerged in a rapid evolution of their economical and legislative environment.To keep or moreover to increase the earnings of their members, cooperatives adopt a policy for ameliorating the production quality. To bring this policy to a successfull issue, they have to suggest their members to adopt a restructuring strategy for their farm estate.This paper presents a vineyard restructure, the simulation of future (DSS) and the decisional impacts of the decision support system.     

Multicriteria approach for intelligent decision support in supervisory control

In the framework of integrated automation, this work concerns the top level of the management and supervision of complex automated systems. When a process is being disturbed, the supervisory function modifies the established production planning, in accordance with different norms and constraints. The operator remains beside the regulated process controls to perform manual operations. The number of potential actions and the conflicting nature of some objectives make his task complex: he must reach quantitative and qualitative objectives with imperfect and temporal information. To assist him, we study a decision support model following a multicriteria approach involving the supervision problem. AI techniques and DSS are used to develop the aid tool. The Spinning Reserve problem encountered by Electricité de France is studied and used as support. To test our concepts, we develop the CASTART experimental support based on a synergy between the user, the problem, and the resolution models.This study is co-financed by the Conseil Régional Nord-Pas de Calais (France) and the University of Valenciennes.     

User-model interaction in decision support systems for risk management

This paper describes and evaluates three different approaches to building decision support systems: the Operations Research/Management Science approach, the Decision Analysis/Multiattribute Utility approach, and the Artificial Intelligence/Expert Systems approach. It evaluates the usefulness of the three approaches for risk management. In particular, it defines evaluation objectives of risk analysts, risk managers, and laypeople and provides a subjective assessment how the three approaches stack up against their objectives. The paper concludes that for most risk management applications a combination of the three approaches would be most desirable.This paper was written under contract No. 2709-85-05 ED ISP D of the European Atomic Energy Community, Commission of the European Communities, Joint Research Centre, Ispra Establishment, Ispra, Italy to the Gemeinschaft für Entscheidungs- und Risikoanalyse, Berlin, West Germany. It was prepared for presentation at the Conference on Operations Research and Multiattribute Decision Analysis held in Passau, April 20–26, 1986. The views and opinions expressed in this paper are solely those of the author.     

Composite alternatives in group decision support

Decision theory models of group decision processes usually assume a given set of alternatives, from which the group has to choose. In realistic group decision situations, however, alternatives are often not specified a priori, but are created during the group process from different components introduced by the group members. This paper develops methods for systematically creating such composite alternatives, also taking into account the necessity to keep both the computational effort and the cognitive load to group members within reasonable limits.Paper presented at the International Conference on Support Systems for Decision and Negotiation Processes DNS-92, Warsaw, 1992.