Ioannis Giannikos

A new model for maximal coverage exploiting GIS capabilities

The representation of demand is a key issue which can significantly affect results in several demand covering models. In this paper we concentrate on the well known Maximal Coverage Location Problem and demonstrate that alternative representations of the demand space may lead to largely fluctuating as well as misleading results which seriously overestimate the real coverage achieved by a specified number of servers. We introduce a new model based on the notion of complementary partial coverage and exploit the capabilities of Geographic Information Systems in order to better represent demand. Results of an empirical study indicate that the proposed model is less susceptible to fluctuations for alternative representations of the demand space and that it provides coverage of a larger proportion of demand than traditional models.

Towards an integrated framework for forest fire control

Abstract This paper presents the development of an integrated system for forest fire control. The system consists of a geographical information system (GIS) module, a mathematical programming (MP) module and a simulation module. The GIS is used to represent geographical information regarding the forest area and to transform the spatial characteristics in a format readable by the MP models. The MP module employs some basic demand covering models to deploy the available fire fighting resources in proper positions so that any forest fire is attacked within a specified time limit. Finally, the simulation module is used to experiment with alternative scenarios and to decide how the fire fighting services should be reallocated according to the development of a particular fire. An application of the method in the area of Parnitha, near Athens, is discussed.

A Hierarchical Location Model for Locating Bank Branches in a Competitive Environment

Recent developments in the provision of banking services are expected to affect the structure and the organization of modern banks significantly. Consequently, it has become necessary for most banks to reorganize their service network. In this context we demonstrate how demand–covering models may be combined with geographical information systems (GIS) to determine the optimal location of bank branches, taking into account the various factors that characterize local conditions within the demand area. The essence of the proposed models is to employ a GIS to represent various criteria concerning the demand for banking services (geographical, social, economic, etc.) as well as the competition in each particular area. This information is then taken into account by appropriate demand–covering models which determine the locations that achieve the maximum capture of the demand. Finally, we present some initial results concerning the application of this approach by a major Greek commercial bank.

A method for improving the accuracy of data mining classification algorithms

In this paper we introduce a method called CL.E.D.M. (CLassification through ELECTRE and Data Mining), that employs aspects of the methodological framework of the ELECTRE I outranking method, and aims at increasing the accuracy of existing data mining classification algorithms. In particular, the method chooses the best decision rules extracted from the training process of the data mining classification algorithms, and then it assigns the classes that correspond to these rules, to the objects that must be classified. Three well known data mining classification algorithms are tested in five different widely used databases to verify the robustness of the proposed method.

A multi-methodological approach to the development of a regional solid waste management system

The management of solid waste at regional level has received considerable attention over the last years. Increased consumption levels are causing an exacerbation of the problem, whereas the sensitivity of the public over environmental issues makes its solution harder. Although the main difficulties in resolving the different occurrences of the problem belong to the realm of policy making, so far the employment of operational research and systems methods seems to adopt a purely technocratic stance, concentrating on the content and understating the solution process. In the different formulations of the problem as static optimization relating to the economics of the location of the treatment facilities and the methods and routes of waste transportation, the dynamics of the issue and the intervention activities are neglected, whereas cognitive and social perspectives of the solution process are objectified and over-rationalized. This paper aims at demonstrating how the solid waste management (SWM) problem and its solution process can be addressed in a more holistic way by adopting a multi-methodological point of view. Towards this end, we present the combined application of soft systems methodology, system dynamics and multi-objective optimization in an action research project for the development of an SWM system for a specific region in Greece.

A fuzzy multicriteria decision‐making methodology for selection of human resources in a Greek private bank

Purpose – The purpose of this paper is to present a fuzzy multicriteria decision‐making (MCDM) methodology for selecting employees.Design/methodology/approach – The methodology is based on the technique for order preference by similarity to ideal solution (TOPSIS) multicriteria decision tool and the algorithm presented by Karsak. Assuming that n are candidates each of whom is evaluated in j criteria, the methodology starts by defining the ideal and the anti‐ideal candidate.Findings – The applicability of the methodology is discussed using real data from a major Greek bank. As a result, it is necessary to consider criteria, criteria weights, and the distances from both the ideal and the anti‐ideal solution in order to select the more appropriate candidate.Research limitations/implications – Modern approaches recognize that selection of human resources is a complex process that involves a significant amount of vagueness and subjectivity, and serious consideration for candidates uncertainties of career life...

Exact and heuristic approaches for the locational planning of an integrated solid waste management system

The management of solid waste has received increased public attention over the last few years as a result of industrialization and its effect on the natural and social environment. The location of proper facilities for treating waste is a sensitive issue that has often caused political and social tension. We study the problem of simultaneous design of a distribution network with central treatment facilities, transfer stations and sanitary landfills, and the coordination of waste flows within this network. In order to determine the number, sizes and locations of the solid waste management (SWM) facilities we propose a MIP formulation of the problem. We present a series of valid inequalities for improving the formulation and discuss their effectiveness. We also present an interchange heuristic that enables us to solve large problems efficiently. Finally, we apply these concepts in an action research project for the development of a SWM system for a specific region in Greece.

Advances in Location Analysis

The field of Location Analysis has been extensively examined by many researchers over the last decade or so. This growth is reflected in the publication of several books and numerous articles that focus on various aspects of location analysis. In particular, new models such as the ordered p-median model have emerged for representing a whole range of location problems in a unified framework. In addition, new algorithms have been developed for solving more complex location problems in realistic time. The application of metaheuristics has created new opportunities for solving problems that, until recently, were considered intractable. All these advances resulted in a multitude of practical applications where location analysis models were formulated in various contexts such as Logistics or Supply Chain Management, to address a number of strategic as well as tactical problems. The above issues were discussed during the 13th Meeting of the European Working Group in Location Analysis (EWGLA) that was organized in the island of Corfu in September 2003. One of the main objectives of the conference was to focus on both quantitative and qualitative aspects of Location Analysis and to encourage the interaction between academics and practitioners within Location Analysis. This edited volume includes some of the papers that were presented during that meeting. After a rigorous refereeing process, twenty four papers were finally accepted for publication in this Feature Issue. These papers cover a wide variety of topics ranging from the derivation of new theoretical results to the application of Location Analysis techniques in specific practical problems. This diversity epitomizes the applicability of Location Analysis and its position within the framework of Operational Research.

CL.E.KMODES: a modified k-modes clustering algorithm

In this paper we present a new method for clustering categorical data sets named CL.E.KMODES. The proposed method is a modified k-modes algorithm that incorporates a new four-step dissimilarity measure, which is based on elements of the methodological framework of the ELECTRE I multicriteria method. The four-step dissimilarity measure introduces an alternative and more accurate way of assigning objects to clusters. In particular, it compares each object with each mode, for every attribute that they have in common, and then chooses the most appropriate mode and its corresponding cluster for that object. Seven widely used data sets are tested to verify the robustness of the proposed method in six clustering evaluation measures.

Developing an integrated solid waste management system in western Greece: a dynamic location analysis

We study the problem of the simultaneous design of a distribution network with central treatment facilities, transfer stations and landfills, and the coordination of waste flows within this network for a long-term planning horizon. We apply these concepts in a research project for the development of a solid waste management system for a specific region in Greece. We then formulate a dynamic mixed integer programming model that minimizes the sum of costs for opening facilities and variable transportation costs related to solid waste flows. Finally, we analyze the results of the model and evaluate the various technologies that may be implemented in the treatment facilities.