Journal of Multi-Criteria Decision Analysis最新文献

This paper presents a new multi-criteria decision-making (MCDM) method, namely the ratio product model (RPM). We first overview two popular aggregating models: the weighted sum model (WSM) and the weighted product model (WPM). Then, we argue that the two models suffer from some fundamental issues mainly due to ignoring the ratio nature of the alternatives' scores with respect to the criteria and the importance weights of the criteria. Building on the notion of compositional data analysis, the developed RPM regards performance scores and criteria weights as compositions, which solves the issues around the WSM and WPM. Using several examples, we show that the WSM and WPM could lead to erroneous conclusions, whereas the RPM could lead to fully reliable conclusions. Since many MCDM methods rely on some aggregation approaches, the proposed method is a significant contribution to the field and puts forward the correct way to analyze decision problems while respecting the nature and constraints of the input data.

Multicriteria decision aid consists of helping decision makers to compare (rank, choose, sort, etc.) different alternatives which are evaluated on conflicting criteria. In the last decades, numerous decision aid methods have been developed. Three main categories of decision aid methods are usually considered: the aggregating, interactive and outranking methods. While aggregation methods produce a complete ranking of the set of alternatives, outranking methods usually allow some pairs of alternatives to remain incomparable. This happens either if the two alternatives present some strong conflicting information or if there are not enough elements in the decision problem to state the preference or indifference between them. A well-known family of outranking procedures are the Promethee methods. The aim of this work is first to provide an analysis of the incomparability relation produced by Promethee I. From our point of view, some shortcomings of this incomparability relation are presented. Then, a new method based on the comparison of weighted coalitions of mono-criterion net flow score differences, called Promethee $��\gamma �$, is proposed. Promethee $��\gamma �$ and Promethee i are then further compared.

Multi-actor multi-criteria analysis is a group decision-making framework that allows multiple stakeholder groups to be involved in the decision-making process, facilitating the understanding of the points of consensus and conflict among the stakeholder groups. Carefully selecting suitable criteria is important as they illustrate the possibly divergent priorities of the respective stakeholder group, and overlooking important criteria can lead to erroneous outcomes. Furthermore, the number of criteria needs specific consideration, as a too large number poses problems for human cognition, but a too small number inaccurately represents the stakeholder's interest. In stakeholder groups with many members, such as those representing citizens, defining a criteria set is likely to be even more complicated. Currently, there is no formal guideline to assist facilitators in defining these criteria sets. In this paper, we propose a novel framework for criteria preprocessing with stakeholder involvement that includes a guideline for firstly selecting criteria into a tentative list and secondly selecting the final criteria set. It provides a procedure on how to determine criteria considering the priorities of stakeholder groups with regard to the context. As a final step, we propose a mathematical model for selecting a number of criteria that are both cognitively manageable and representative for the participants' priorities. Based on the principles of the Pareto analysis, as well as the cognitive judgment theory “magic number seven plus or minus two”, a recommendation list of the criteria is generated. It prevents key criteria from being omitted while at the same time limiting the overall number of criteria. This framework is applied to a social decision-making case for construction logistics, and the results are compared with the conventional approach of criteria definition.

Walking School Bus (WSB) has been recognised as an innovative solution to promote walking to school, bringing a wide spectrum of benefits, including: health benefits from the physical exercise, social skills and traffic reduction. To facilitate the success of WSB, one vital element is its route planning, which directly affects the catchment for the service and the realisation of all the potential benefits. Previously, time has been the only factor that has been considered in WSB routing problems. Other important factors including air quality, safety and comfort will also be considered in this paper. Air quality along a WSB route is important to help realise the health benefits of walking. Traffic safety has been the biggest barrier to walking to school and must be addressed in planning a WSB route. Ensuring children have an enjoyable and comfortable experience is vital for the sustainability and success of WSB. A walking network is introduced to enable modelling pedestrian movements in detail, including walking movements on different sides of the road and crossing movements. This approach enables detailed route-based analysis to assess the localised effect of air quality on pollutant dose. We define walkability as a measure of children's needs in safety and comfort, which can also be assessed in detail on each route. We propose a multi-objective optimisation model to generate efficient WSB routes with three objectives representing the potential benefits of WSB: (1) to minimise time; (2) to minimise pollutant dose; and (3) to maximise walkability. We apply our model to a selected school in Bradford in the UK, generating three WSB lines following efficient routes. These lines go through a predetermined sequence of ‘WSB Stops’, with the final stop as the school. All children within the catchment area will be able to join a WSB within 1–2 min walk from their home to the nearest stop. Our multi-objective WSB route planning model is highly transferable to any selected school in any WSB targeted area. Planners will be able to select a combination of WSB lines to offer, based on the requirement of coverage area and resource availability.

Pharmaceutical Supply Chain (PSC) plays a critical role in the healthcare sector. This study identifies, validates, and prioritises the factors that play a crucial role in PSC performance, adopting a threefold approach. In the first stage performance, indicators were identified through an extensive review of the literature. With the help of expert opinion, the identified factors were validated and then categorised based on technological—organisational—environmental (TOE) and supply chain (SC) theories to propose a framework. The Pakistani Pharmaceutical sector firms were selected to investigate the cause and effect relationship among the factors, their interdependencies, and impact on overall PSC performance. This investigation was supported by a novel integrated analytic model composed of best worst method (BWM), decision-making trial and evaluation laboratory (DEMATEL), and analytical network process (ANP) methods. The results indicate that ‘human resource skills, competencies, and involvement’, ‘process improvement and healthcare reform, and manufacturing’, and ‘distribution and inventory management’ are the top three factors that have a high impact on the overall PSC performance. This study outcome help inform decision-makers and managers in the healthcare sector in formulating strategies to improve their SC performance.

Multiple attribute decision-making (MADM) tools can effectively support the decision analysts in selecting the best alternative among many, ranking the alternatives in decreasing or increasing order of preference, or allocating the alternatives into pre-defined ordered classes/categories. Even though the literature provides the analyst with precious sorting-based MADM tools such as PROMSORT, UTADIS, AHPSort, TOPSISsort, and so forth, the majority of the methods can be found complex and hard to be understood by the researchers and practitioners who are not familiar with the mathematical notions and computations of MADM (distance calculation, threshold and preference function determination, and so on). To provide a simpler but powerful MADM tool aiming at sorting the alternatives into classes, this study proposes a sorting-based additive ratio assessment algorithm which is called ARASsort. For limiting (interval-based) and central (reference-based) profiles describing the categories, we have developed two algorithms: ARASsort-lp and ARASsort-cp, respectively. Their applicability was shown in two examples: green supplier evaluation and economic freedom evaluation of countries. The validity of algorithms was presented by demonstrating the class assignment similarities between the results obtained by ARASsort, VIKORsort, and TOPSISsort. The findings show that ARASsort works well because it shows a higher level of class assignment similarities with the other methods.

The objective of the study was to assess the optimum frying condition of fish considering the multiple perspectives (retention of nutritional quality indices [NQI], reduction of preparation time, and improvement of health benefit) to satisfy consumer-preferred sensory attributes by controlling the most impactful process variables (temperature, time, and oil amount). The multi-criteria decision-making (MCDM) approach is appropriate to handle the numerous conflicting criteria and numerous multiple objectives. First, an artificial neural network (ANN) model was developed to build a non-linear correlation between the cooking process parameters and NQI by an automatic exhaustive search of all available algorithms and activation functions. All the NQI are conflicting in nature. Therefore, the ANN-based multi-objective genetic algorithm was implemented to obtain the Pareto optimal solutions to improve all NQI simultaneously. Five optimised conditions were selected amongst the Pareto optimal solutions, satisfying the above-mentioned multiple criteria. Finally, a well-known MCDM approach, the analytical hierarchy process (AHP), was applied for sensory analysis to evaluate the overall acceptance of the optimised conditions based on the relative importance of consumers' general sensory modalities (flavour, colour & appearance, and taste). Furthermore, the following condition (140.01°C, 7.62 min, 47.87 ml oil/kg of fish) was selected as the most accepted in terms of all quality attributes that may be implemented as the standard condition in domestic and industrial purposes.

Solving non-cooperative zero-sum multi-objective Games (zsMOGs), under undecided objective preferences results, for each of the players, in a Set of Rationalizable Strategies (SRS) to choose from. First, this paper deals with finding for each of the players a preferred subset of such rationalizable strategies based on a-priori incorporation of partial preferences of the decision-makers using secondary criteria. The obtained subset is termed the Set of Preferred Strategies (SPS). Here, a novel archive-based co-evolutionary algorithm is suggested to search for the SPS for each of the players. An academic example is suggested to demonstrate and validate the algorithm. It concerns a zsMOG that involves two adversarial planar manipulators. Based on a theorem that is proven here, a theoretic reference SRS is found for each of the players. This reference SRS is applied to find a reference SPS, which is used for validating the algorithm. Next, a comparison study is performed between the proposed archive-based co-evolutionary algorithm and an elite-based version of this algorithm. The results clearly show that the archive-based algorithm is superior to the elite-based version, yielding results that correspond well to the theoretic sets.

This study aims to develop a pipeline for identifying and prioritising the processes to include in business process management (BPM) initiatives by considering the obstacles for giving equal importance to the processes performed in businesses. The paper proposes the use of a process classification framework as a reference for process identification and fuzzy multi-criteria decision-making methods for prioritising the processes. A real-life application is presented, which adopts APQC Process Identification Framework, Fuzzy-SWARA for weighting the criteria, and six additional methods for prioritising the processes. The approach would assist the executives in maintaining the BPM lifecycle by presenting a roadmap, especially for organisations that do not have much experience in this field. Methodological depth, richness and recency would provide guidelines for investigating the best set of processes to include in the architecture initially, not in the analysis or redesign phases.

Forest road building is experiencing a period of expansion. It is linked to better resource extraction and transportation and higher ease of access for inhabitants. This paper discusses the problem of evaluating a forest road network in the Hyrcanian forest in northern Iran. This includes the requirements that forest managers must consider, such as economic and environmental criteria. In addition, opportunities and risks of forest road building are also considered. A multi-methodology decision-making approach is proposed to solve the problem. In light of the results, the proposed approach is reliable and flexible for use in similar cases. Using the proposed approach can structure and facilitate the decision-making process for the managers.