19 This study introduces a new open source software framework to support bottom-up environmental 20 systems planning under deep uncertainty with a focus on many-objective robust decision making 21 (MORDM), called OpenMORDM. OpenMORDM contains two complementary components: (1) a 22 software application programming interface (API) for connecting planning models to computational 23 exploration too...

In a bilevel decision problem, the leader at the upper level attempts to optimize his/her objective, the follower at the lower level tries to find an optimized strategy according to each of possible decisions made by the leader. A bilevel decision problem may involve fuzzy demands which appear either in the objective functions or constraints of the leader or the follower or both. Furthermore, t...

My research is aimed at finding efficient coordination methods for multi-objective collaborative multi-agent decision theoretic planning. Key to coordinating efficiently in these settings is exploiting loose couplings between agents. We proposed two algorithms for the case in which the agents need to make a single collective decision: convex multiobjective variable elimination (CMOVE) and varia...

Concave properties play a dominate role in solving both classic and fuzzy optimization problems. However, since fuzzy problems are generally represented by sets, not crisp numbers, various aggregation schemes are needed to manipulate and to combine the different elements in a fuzzy optimization problem. Based on these different aggregations, various concavity properties can be formulated and ex...

In multi-objective decision planning and learning, much attention is paid to producing optimal solution sets that contain an optimal policy for every possible user preference profile. We argue that the step that follows, i.e, determining which policy to execute by maximising the user’s intrinsic utility function over this (possibly infinite) set, is under-studied. This paper aims to fill this g...

Investment in landscapes to achieve outcomes that have multiple environmental benefits has become a major priority in many countries. This gives rise to opportunities for mathematical programming methods to provide solutions on where investments could be made on the landscape, to maximise multiple environmental benefits. The problem was formulated as a multi-objective integer programming model,...

Two approaches to formal multiple objective decision analysis are described , illustrated and compared. These two approaches, generating techniques and goal programming, are illustrated by the solution of a simple numerical example. This solution combined with some lessons from the field of psychology provide a basis for some judgments on the relative merits of the approaches.

In this paper we describe various visualization techniques which have been used or which might be useful in the multiple objective decision making framework. Several of the ideas originate from statistics, especially multivariate statistics. Some techniques are simply for illustrating snapshots of a single solution or a set of solutions. Others are used as an essential part of the human-compute...

Clustering is an important problem in knowledge discovery and decision making. In this study, a multi-objective genetic algorithm (MOGA) is used to search for well separated clusters and each evolved solution is evaluated by both data-driven and human-driven metrics developed for this study. The proposed system in this paper also allows the decision maker to navigate non-dominated solutions and...

The importance of the precautionary principle in public health was highlighted in France after the HIV contamination of blood products used for transfusion. However, the definition of this principle, its objectives, the way in which it should be applied, and its consequences had not been considered previously. The question as to whether the application of the precautionary principle is appropri...