Mathematical Model and Stochastic Multi-Criteria Acceptability Analysis for Facility Location Problem

This paper studies a real-life public sector facility location problem. The problem fundamentally originated from the idea of downsizing the number of service centres. However, opening of new facilities is also considered in case the current facilities fail to fulfil general management demands. Two operation research methodologies are used to solve the problem and the obtained results are compared. First, a mathematical programming model is introduced to determine where the new facilities will be located, and which districts get service from which facilities, as if there were currently no existing facilities. Second, the Stochastic Multi-criteria Acceptability Analysis-TRI (SMAA-TRI) method is used to select the best suitable places for service centres among the existing facilities. It is noted that the application of mathematical programming model and SMAA-TRI integration approach on facility location problem is the first study in literature. Compression of outcomes shows that mixed integer linear programming (MILP) model tries to open facilities in districts which are favoured by SMAA-TRI solution.</span

Decision Support Systems for Sustainable Logistics: A Review and Bibliometric Analysis

Purpose: Decision-making in logistics is an increasingly complex task for organizations as these involve decisions at strategic, tactical and operational levels coupled with the triple bottom line (TBL) of sustainability. Decision support systems (DSS) played a vital role in arguably solving the challenges associated with decision making in sustainable logistics. This review is a systematic attempt to explore the current state of the research in the domain of DSS for logistics while considering sustainability aspects. Design/methodology/approach: A systematic review approach using a set of relevant keywords with several exclusion criteria was adopted to identify literature related to DSS for sustainable logistics. A total of 40 papers were found from 1994 to 2015, which were then analysed along the dimensions of publishing trend, geographic distribution and collaboration, the most influential journals, affiliations and authors as well as the key themes of identified literature. The analysis was conducted by means of bibliometric and text mapping tools, namely BibExcel, gpsvisualizer, and VOSviewer. Findings: The bibliometric analysis showed that DSS for sustainable logistics is an emerging field; however, it is still evolving but at a slower pace. Furthermore, most of the contributing affiliations belong to the United States and the United Kingdom. The text mining and keyword analysis revealed key themes of identified papers. The inherent key themes were decision models and frameworks to address sustainable logistics issues covering transport, distribution and third party logistics. The most prominent sustainable logistics issue was carbon footprinting. Social impact has been given less attention in comparison to economic and environmental aspects. The literature has adequate room for proposing more effective solutions by considering various types of MCDA (multi-criteria decision analysis) methods and DSS configurations while simultaneously considering economic, environmental and social aspects of sustainable logistics. Moreover, the field has potential to include logistics from wide application areas including freight transport through road, rail, sea, air as well as inter-modal transport, port operations, material handling and warehousing. Originality/value: To the best of the authors’ knowledge, this is the first systematic review of DSS for sustainable logistics using bibliometric and text analysis. The key themes and research gaps identified in this paper will provide a reference point that will encourage and guide interested researchers for future study, thus aiding both theoretical and practical advancements in this discipline

Decision support systems for sustainable logistics: A review and bibliometric analysis

Purpose: Decision-making in logistics is an increasingly complex task for organizations as these involve decisions at strategic, tactical and operational levels coupled with the triple bottom line (TBL) of sustainability. Decision support systems (DSS) played a vital role in arguably solving the challenges associated with decision making in sustainable logistics. This review is a systematic attempt to explore the current state of the research in the domain of DSS for logistics while considering sustainability aspects. Design/methodology/approach: A systematic review approach using a set of relevant keywords with several exclusion criteria was adopted to identify literature related to DSS for sustainable logistics. A total of 40 papers were found from 1994 to 2015, which were then analysed along the dimensions of publishing trend, geographic distribution and collaboration, the most influential journals, affiliations and authors as well as the key themes of identified literature. The analysis was conducted by means of bibliometric and text mapping tools, namely BibExcel, gpsvisualizer, and VOSviewer. Findings: The bibliometric analysis showed that DSS for sustainable logistics is an emerging field; however, it is still evolving but at a slower pace. Furthermore, most of the contributing affiliations belong to the United States and the United Kingdom. The text mining and keyword analysis revealed key themes of identified papers. The inherent key themes were decision models and frameworks to address sustainable logistics issues covering transport, distribution and third party logistics. The most prominent sustainable logistics issue was carbon footprinting. Social impact has been given less attention in comparison to economic and environmental aspects. The literature has adequate room for proposing more effective solutions by considering various types of MCDA (multi-criteria decision analysis) methods and DSS configurations while simultaneously considering economic, environmental and social aspects of sustainable logistics. Moreover, the field has potential to include logistics from wide application areas including freight transport through road, rail, sea, air as well as inter-modal transport, port operations, material handling and warehousing. Originality/value: To the best of the authors’ knowledge, this is the first systematic review of DSS for sustainable logistics using bibliometric and text analysis. The key themes and research gaps identified in this paper will provide a reference point that will encourage and guide interested researchers for future study, thus aiding both theoretical and practical advancements in this discipline

σ-µ efficiency analysis: A new methodology for evaluating units through composite indices

We propose a new methodology to employ composite indicators for performance analysis of units of interest using Stochastic Multiattribute Acceptability Analysis. We start evaluating each unit by means of weighted sums of their elementary indicators in the whole set of admissible weights. For each unit, we compute the mean, µ, and the standard deviation, σ, of its evaluations. Clearly, the former has to be maximized, while the latter has to be minimized as it denotes instability in the evaluations with respect to the variability of weights. We consider a unit to be Pareto-Koopmans efficient with respect to µ and σ if there is no convex combination of µ and σ of the rest of the units with a value of µ that is not smaller, and a value of σ that is not greater, with at least one strict inequality. The set of all Pareto-Koopmans efficient units constitutes the first Pareto-Koopmans frontier. By removing this set and computing the efficiency frontier for the rest of the units, one could obtain the second Pareto-Koopmans frontier. Analogously, the third, fourth and so on Pareto-Koopmans frontiers can be defined. This permits to assign each unit to one of this sequence of Pareto-Koopmans frontiers. We measure the efficiency of each unit not only with respect to the first Pareto-Koopmans frontier, as in the classic Data Envelopment Analysis, but also with respect to the rest of the frontiers, thus enhancing the explicative power of the proposed approach. To illustrate its potential, we apply it to a case study of world happiness based on the data of the homonymous report, annually produced by the United Nations’ Sustainable Development Solutions Network

σ-µ efficiency analysis: A new methodology for evaluating units through composite indices

We propose a new methodology to employ composite indicators for performance analysis of units of interest using and extending the family of Stochastic Multiattribute Acceptability Analysis. We start evaluating each unit by means of weighted sums of their elementary indicators in the whole set of admissible weights. For each unit, we compute the mean, �, and the standard deviation, �, of its evaluations. Clearly, the former has to be maximized, while the latter has to be minimized as it denotes instability in the evaluations with respect to the variability of weights. We consider a unit to be Pareto-Koopmans efficient with respect to � and � if there is no convex combination of � and � of the rest of the units with a value of � that is not smaller, and a value of � that is not greater, with at least one strict inequality. The set of all Pareto-Koopmans efficient units constitutes the first Pareto-Koopmans frontier. In the spirit of context-dependent Data Envelopment Analysis, we assign each unit to one of the sequences of Pareto-Koopmans frontiers. We measure the local efficiency of each unit with respect to each frontier, but also its global efficiency taking into account all feasible frontiers in the

Desarrollo de una metodología para la introducción de productos nuevos soportada en el método Delphi y el SMAA

Ingeniero (a) IndustrialPregrad

Decision support for centralizing cargo at a Moroccan airport hub using stochastic multicriteria acceptability analysis

The geographical location of Morocco places it at the heart of important sea, air, rail and motorway transport routes between four continents. In this study we evaluate different alternatives to centralize multimodal cargo at a Moroccan airport hub. The choice depends on different socio-economical criteria, the geographical location, and the environmental impacts. Some of the criteria can be measured quantitatively, while for others only qualitative assessment is feasible. Furthermore, significant uncertainty is present in both the criteria measurements and the preferences. We aided this decision process using Stochastic Multicriteria Acceptability Analysis (SMAA). SMAA is a method that allows the representation of a mixture of different kinds of uncertain, imprecise and partially missing information in a consistent way. The results indicated that two of the alternatives, Benslimane and Casablanca, were superior. As a result of the analysis, the National Airport Authority of Morocco started negotiations with investors to develop the hub at Benslimane.Transportation Air cargo hub Decision support Stochastic multicriteria acceptability analysis

Sustainability in design: now! Challenges and opportunities for design research, education and practice in the XXI century

Copyright @ 2010 Greenleaf PublicationsLeNS project funded by the Asia Link Programme, EuropeAid, European Commission