Comparison of multi-criteria decision analytical software for supporting environmental planning processes

In this paper, we analyze 23 multi-criteria decision analysis software tools in terms of their applicability to support environmental planning processes. Our aim is to survey what kind of software is available, and compare the features they provide to meet the characteristics of environmental problems. Our focus is on useful or innovative features of the software from the viewpoint of supporting practitioners to systematically analyze and compare alternatives in environmental planning. The results can be utilized for selecting the most suitable software for supporting the needs of the environmental cases, but also for identifying good practices and innovative implementation solutions for software development.     

Integrating new information and communication technologies in a group decision support system

We view group decision making as a collaborative process, where decision makers can establish a common belief on the dimensions of the problem by following a series of well-defined communicative actions. Having first defined these actions, this paper reports on the exploitation of recent advances in information and communication technology, which can be used to: (i) remove the communication impediments among spatially dispersed decision makers; (ii) efficiently elicit and represent the domain of knowledge; (iii) develop efficient mechanisms to structure and consistently maintain the decision analysis; and (iv) automate the decision making process itself. Automation concerns coherence and consistency checking, detection of contradictions, truth maintenance, and information retrieval techniques.     

A web-based decision support system for multi-criteria inventory classification using fuzzy AHP methodology

We propose an inventory classification system based on the fuzzy analytic hierarchy process (AHP), a commonly used tool for multi-criteria decision making problems. We integrate fuzzy concepts with real inventory data and design a decision support system assisting a sensible multi-criteria inventory classification. We report on a study conducted in a small electrical appliances company and validate the design of the proposed multi-criteria inventory classification system and its underlying fuzzy AHP model.     

JUDGES: A descriptive group decision support system for the ranking of items

A set of tools for group decision support are presented. Decision problems involving several decision makers, here-after called judges, that have to rank several alternatives, are considered. The toolbox is called JUDGES. It includes the four following procedures:

• - a hierarchical representation of the judges allows to display the existing conflicts between groups of judges,

• - enhanced box-plots representations of the alternatives are generated in order to detect those that are responsible for the major conflicts,

• - specific advice is issued to each judge in order to reach more easily a consensus,

• - a general framework for a pairwise group preference structure is proposed, and can be used to finalise the decision.

These procedures are embedded in an interactive software, implemented on micro-computer, which currently simulates the use on a network. Actual network implementation is foreseen in the near future. Several applications are presented and future developments are discussed.

A distance-based group decision-making methodology for multi-person multi-criteria emergency decision support

In this paper, a distance-based group decision-making (GDM) methodology is proposed to solve unconventional multi-person multi-criteria emergency decision-making problems. In this model, some decision-makers are first identified to formulate a group decision-making framework. Then a standard multi-criteria decision-making (MCDM) process is performed on specific decision-making problems and different decision results are obtained from different decision-makers. Finally, these different decision results are aggregated into a group consensus to support the final decision-making. For illustration and verification purposes, a numerical example and a practical unconventional emergency decision case are presented. Experimental results obtained demonstrate that the proposed distance-based multi-criteria GDM methodology can improve decision-making objectivity and emergency management effectiveness.     

A robust hybrid multi-criteria decision making methodology for contractor evaluation and selection in third-party reverse logistics

Due to green legislations, industries track the used products through reverse logistics contractors. A reverse logistics programme offers significant cost savings in procurement, transportation, disposal and inventory carrying. Since reverse logistics operations and the supply chains they support are considerably more complex than traditional manufacturing supply chains, it can be offered to third party contractors. But availability of more number of contractors make evaluating and selecting the most efficient Reverse Logistics Contractor (RLC) a challenging task and treated as a multi-criteria decision making problem. In this paper, a hybrid method using Analytical Hierarchy Process (AHP) and the Fuzzy Technique for Order Preference by Similarity to Ideal Solutions (TOPSIS) is proposed. AHP is used to obtain the initial weights and Fuzzy TOPSIS is used to get the final ranking. A case study demonstrates the application of the proposed method. Finally sensitivity analysis is carried out to confirm the robustness.     

Analysis of heuristic validity,efficiency and applicability of the profile distance method for implementation in decision support systems

This article seeks to enhance acceptance of the profile distance method (PDM) in decision support systems. The PDM is a multiple attributive-based decision making as well as a multiple method approach to support complex decision making and uses a heuristic to avoid computationally complex global optimization. We elaborate on the usability of the method and question the heuristic used. We present a bi-section algorithm, which efficiently supports the discovery of transition profiles needed in a user-friendly and practical application of the method. Additionally, we provide empirical evidence showing that the proposed heuristic is efficient and delivers results within 5% of the global optimizer for a wide range of datasets.     

A consistency and consensus based decision support model for group decision making with multiplicative preference relations

In group decision making (GDM) with multiplicative preference relations (also known as pairwise comparison matrices in the Analytical Hierarchy Process), to come to a meaningful and reliable solution, it is preferable to consider individual consistency and group consensus in the decision process. This paper provides a decision support model to aid the group consensus process while keeping an acceptable individual consistency for each decision maker. The concept of an individual consistency index and a group consensus index is introduced based on the Hadamard product of two matrices. Two algorithms are presented in the designed support model. The first algorithm is utilized to convert an unacceptable preference relation to an acceptable one. The second algorithm is designed to assist the group in achieving a predefined consensus level. The main characteristics of our model are that: (1) it is independent of the prioritization method used in the consensus process; (2) it ensures that each individual multiplicative preference relation is of acceptable consistency when the predefined consensus level is achieved. Finally, some numerical examples are given to verify the effectiveness of our model.     

A decision support system for automotive product planning and competitive market analysis

A decision support system (DSS) for automotive product marketing, design and manufacturing in China is presented in this paper. The DSS is developed as a tool to support product planning, competitive market analysis, supply chain analysis and subsequent manufacturing systems planning and deployment. The system consists of a number of automotive related databases which provide information about manufacturers' performance in each market segment as well as production information of all existing market players in the Chinese auto industry. Product planning, one of the key modules of the DSS prototype, is highlighted in this paper. It supports decision makers in determining suitable strategies for market entry by analyzing existing competitors' status, growth estimation of each market segment, and competitive market analysis for new vehicle products. A case study for new market entry is included here to demonstrate the feasibility and effectiveness of the proposed methodology.     

A decision support system for strategic planning in large-scale marketing channels: An example in the tile industry

This paper presents a decision support system for strategic planning in marketing channels. A dynamic model of the marketing channel is employed which comprises manufacturer and retailer levels. Decision making is achieved through a game theoretical inference mechanism in which each player (manufacturer/retailer) optimises for a long-term profit maximisation objective. Both historical data and managerial expertise are used for the parameterisation of the system's knowledge base. The decision support system provides a forecast of profit and sales and computes pricing and shelf space allocation strategies that maximise long-term profit. It offers facilities such as the study of coalitions, long-term decision-making in all phases of a product's life cycle, the impact of pricing, allocation strategies, production expansion, cost regulation, and others. The operationality of the system is illustrated in decision-making situations in the tile industry.     

A decision support system for the planning of the workload on a grain terminal

Ships, loaded with agricultural products, are handled by GEM at three different terminals in the port of Rotterdam. Each terminal consists of several berths and has both floating equipment and shore equipment. This paper describes the terminal system, the planning process and a menu driven computer planning model of the system. The planning model is split up into a first phase, in which berths are allocated, and a second phase, in which unloading equipment is assigned. The user of the model has the opportunity to manipulate several penalties and assign preferences to berths.     

GAHPSort: A new group multi-criteria decision method for sorting a large number of the cloud-based ERP solutions

Companies are increasingly introducing cloud-based ERP systems as a solution for integrating all-in-one business functions into the Internet. To support this decision, this paper proposes the Group Analytic Hierarchy Process Sorting (GAHPSort) method, which extends the classical AHP for sorting problems with a large number of alternatives. Our study is specifically based on two steps: Firstly, the cloud-based ERP vendors are sorted with GAHPSort into two classes: accepted or rejected. Secondly, a single solution is selected with Analytic Network Process (ANP) among accepted vendors. To validate our model, we present the results obtained from a real case study.     

An intelligent decision support system for supply,distribution, and marketing planning

The paper focuses on a new and successful application of an optimization-based decision support system (DSS) in the Petroleum Industry. It involves the design, development and implementation of a model and computer system to address the complex short-term planning and operational issues associated with the supply, distribution and marketing of refined petroleum products. This has evolved into an intelligent DSS that uses the tools of Knowledge Engineering and Expert Systems to build an effective, integrated DSS. Several unique modeling features, hitherto untried in any major modeling effort, have been successfully implemented in a Network Optimization framework. The use of a fourth generation modeling language called GENASYS has been instrumental in capturing the intricacies of the network model and facilitates creating new model structures for various parametric changes. Concepts from Knowledge Based Systems and Artificial Intelligence applied in setting up Exception Reports through the use of production rules are another major characteristic of this application. The impact of this decision support system on integrated short-term planning and decision making and in stimulating changes in the attitudes and environment of the users and management is extensive.This research was supported in part by the Center for Business Decision Analysis, the Hugh Roy Cullen Centennial Chair in Business Administration, and the Office of Naval Research under contract N00014-78C-0222. Reproduction in whole or in part is permitted for any purpose of the U.S. Government.     

Group decision process support system for regional planning—A perspective from Japan

Regional planning has been regarded as a design activity. Usually planners focus on physical design rather than on societal issues. Nowadays, mass communication, environmental issues and social awareness lead to often complex and conflicting needs and interests of the public in regional planning. This paper focuses on the regional planning as a group problem solving process from the view of information processing. It offers an analysis of the causes of conflicts in the group decision process, and defines the characteristics of group decision process support systems     

A decision support system for paper making based on simulation and optimization

In this paper a model-driven decision support system related to paper making is introduced. The intention is to emphasize the necessity of coupling different modeling techniques, multiobjective optimization, and software engineering in order to make the end user application realistic, practical and usable. Firstly the paper making process and selected aspects concerning its mathematical modeling, numerical simulation, and multiobjective optimization are introduced, then the related computerized system, called a virtual paper making line, is described. In addition, the associated decision support system, which provides a suitable level of automation to improve the quality of decision making and support the user’s expertise is discussed. Finally, an example presents different ways of using such a software tool.     

A method for fuzzy group decision making based on induced aggregation operators and Euclidean distance

In this paper, we present the fuzzy‐induced Euclidean ordered weighted averaging distance (FIEOWAD) operator. It is an extension of the ordered weighted averaging (OWA) operator that uses the main characteristics of the induced OWA (IOWA), the Euclidean distance and uncertain information represented by fuzzy numbers. The main advantage of this operator is that it is able to consider complex attitudinal characters of the decision maker by using order‐inducing variables in the aggregation of the Euclidean distance. Moreover, it is able to deal with uncertain environments where the information is very imprecise and can be assessed with fuzzy numbers. We study some of its main properties and particular cases such as the fuzzy maximum distance, fuzzy minimum distance, fuzzy‐normalized Euclidean distance (FNED), fuzzy‐weighted Euclidean distance (FWED), and fuzzy Euclidean ordered weighted averaging distance (FEOWAD) operator. Finally, we present an application of the operator to a group decision‐making problem concerning the selection of strategies.     

The effects of decision support and task contingencies on model formulation: A cognitive perspective

This paper takes a cognitive cost-benefit approach to understanding model formulation. Work in the behavioral decision literature on the role of effort and accuracy in choice tasks indicates that effort, or cognitive cost, is a key factor in understanding decision behavior. However, the model formulation literature does not discuss how effort interacts with other factors, such as task complexity and decision aids, to influence model formulation. In this paper, based on the work on the cost-benefit theories of cognition, we posit that two types of effort, namely that associated with building or formulating a model and that associated with utilizing that model in the solution of a problem, will influence model formulation. We then examine how the methods used in the behavioral decision making literature and the reported findings concerning the interaction of effort with task and decision aids can be utilized to understand model formulation.     

A fuzzy decision support system for digital camera selection based on user preferences

Mobile phones have been the most rapidly spreading development in the field of communication and information technologies over the past decades. Nowadays, digital cameras have taken their place. The wide product range in the market, each with numerous heterogeneous technical attributes, complicates the selection of the most convenient camera for end-users. The aim of this work is to provide end-users with a decision support framework for selecting the best digital camera according to their preferences. End-users and photography experts use subjective assessments when determining their requirements and making their evaluations. The proposed decision support tool is built on the basis of fuzzy set theory. The imprecision of the subjective assessments are transformed to fuzzy triangular numbers. The fuzzy analytic hierarchy process (FAHP) and fuzzy compromise programming methodologies are applied in order to determine the relative weights of sub-criteria and criteria and to rank the digital camera alternatives, respectively.     

udpSkeduler: A Web architecture based decision support system for course and classroom scheduling

A key process for post-secondary educational institutions is the definition of course timetables and classroom assignments. Manual scheduling methods require enormous amounts of time and resources to deliver results of questionable quality, and multiple course and classroom conflicts usually occur. This article presents a scheduling system implemented in a Web environment. This system generates optimal schedules via an integer-programming model. Among its functionalities, this system enables direct interaction with instructors in order to gather data on their time availability for teaching courses. The results demonstrate that significant improvements over the typical fully manual process were obtained.     

Testing the scenario hypothesis: An experimental comparison of scenarios and forecasts for decision support in a complex decision environment

Decision support tools are known to influence and facilitate decisionmaking through the thoughtful construction of the decision environment. However, little research has empirically evaluated the effects of using scenarios and forecasts. In this research, we asked participants to recommend a fisheries management strategy that achieved multiple objectives in the face of significant uncertainty. A decision support tool with one of two conditions—Scenario or Forecast—encouraged participants to explore a large set of diversified decision options. We found that participants in the two conditions explored the options similarly, but chose differently. Participants in the Scenario Condition chose the strategies that performed well over the full range of uncertainties (robust strategies) significantly more frequently than did those in the Forecast Condition. This difference seems largely to be because participants in the Scenario Condition paid increased attention to worst-case futures. The results offer lessons for designing decision support tools.