Journal of Multi-Criteria Decision Analysis最新文献

In this manuscript, we question the capacity of well-known inconsistency indices to measure, in a cardinal sense, the inconsistency of preferences. We argue that, at present, axiomatic properties of inconsistency indices only guarantee the good behaviour of an index when it comes to rank matrices according to their inconsistency, and the measurement of the intensity of preferences is not guaranteed. We propose to adapt the concept of measurability, established by Multiple Attribute Value Theory, to define measurable inconsistency indices. We conclude by presenting some methods to obtain measurable inconsistency indices.

Scenarios have been used in risk management for many years, first in scenario planning to identify risks and their possible impacts, which may then be explored using quantitative risk analysis. Qualitative scenario planning has been used in supporting decision-making and strategic deliberations generally, and as a tool in problem formulation for quantitative multi-criteria decision analysis (MCDA) studies. Until relatively recently, however, scenario thinking has not been more fully combined with quantitative MCDA studies. There are issues to overcome in forming meaningful quantitative comparisons between scenarios and in presenting the results to decision-makers in ways that help them reach a conclusion which they judge to be requisite. This paper discusses these issues and offers a research agenda.

This paper addresses an inconsistency in various definitions of supported non-dominated points within multi-objective integer linear optimization problems (MOILPs). MOILP problems are known to contain supported and unsupported non-dominated points, with the latter typically outnumbering the former. Supported points are, in general, easier to determine, can serve as representations and are used in two-phase methods to generate the entire non-dominated point set. Despite their importance, several different characterizations for supported efficient solutions (and supported non-dominated points) are used in the literature. While these definitions are equivalent for multi-objective linear optimization problems, they can yield different sets of supported non-dominated points for MOILP problems. We show by an example that these definitions are not equivalent for MOILP or general multi-objective optimization problems. Moreover, we analyse the structural and computational properties of the resulting sets of supported non-dominated points. These considerations motivate us to summarise equivalent definitions and characterizations for supported efficient solutions and to introduce a distinction between supported and weakly supported efficient solutions.

In proton therapy treatment planning, the aim is to ensure tumour control while sparing the various surrounding risk structures. The biological effect of the irradiation depends on both physical dose and linear energy transfer (LET). In order to include LET alongside physical dose in plan creation, we propose to formulate the proton treatment planning problem as a particularly structured multi-criteria bi-level optimization problem, which we call hierarchical. We show that the hierarchical multi-criteria bi-level problem can be reduced to a standard multi-criteria optimization (MCO) problem employing a specific domination cone. As the unfavourable properties of this cone prohibit a direct application of standard MCO solution methods, we further illustrate how a more convenient approximate cone can be constructed. Based on the found reduction to a standard MCO problem, we then describe a novel approach to calculate a representation of the non-dominated points for the hierarchical multi-criteria bi-level problem. As a point of reference, we also discuss a second, more brute-force approach. We apply both approaches to a prostate and a head and neck case and compare the results.

Azzini, I. and G. Munda. 2025. “Sensitivity and Robustness Analyses in Social Multi-Criteria Evaluation of Public Policies” Journal of Multi-Criteria Decision Analysis 32: e70006

Table 1 in Azzini and Munda (2025) was incorrect. The correct table is listed below:

We apologize for this error.

We review the contributions to research of Theo Stewart. We distinguish two important streams of research: (1) His work supporting applications of multi-criteria decision analysis and multi-objective optimization often seeking to integrate several related fields and different schools, (2) His applied work based on the use of multi-criteria decision analysis and multi-objective optimization, notably dealing with environment, energy, sustainability, land use, and fisheries.

In an uncertain and competitive world, operational activities need to be aligned with company strategies. In terms of supply chain management, several strategies have been discussed in the literature to improve the performance of a company. In this context, this study presents a supplier selection problem in the context of strategic operations. The study considers classical objectives of manufacturing strategy to support the supplier selection problem for a food company. The study contributes to the literature by discussing and illustrating the use of Decision Support Systems (DSS) to support strategic Multi-Criteria Decision Making/Aiding problems. The novelty of the study is that it considers the strategic operations objectives in a real supplier selection problem. Hence, five real suppliers are considered and are evaluated against seven criteria, namely: Price, Freight, Accuracy, Quality, Flexibility, Lead Time, and Promptness, to attend to strategic operations. The FITradeoff Decision Support System (DSS) is applied to solve this problem. The DSS presents both paradigms for preference modelling i.e., elicitation by decomposition and holistic evaluation. These give more flexibility to Decision-Makers. Therefore, this study focusses on illustrating the use of this DSS to support a supplier selection process from the strategic operations perspective.