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...

Sequential decision-making problems with multiple objectives arise naturally in practice and pose unique challenges for research in decision-theoretic planning and learning, which has largely focused on single-objective settings. This article surveys algorithms designed for sequential decision-making problems with multiple objectives. Though there is a growing body of literature on this subject...

Decision-making tasks sometimes involve soft objectives. They are soft in the sense that they contain uncertainty, imprecision or vagueness. For example, decisions on built environment aim to maximize comfort or other experiential qualities. Pareto-optimal solutions to such problems can be found using multi-objective evolutionary search together with other soft computing methods. Beyond optimal...

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...

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,...

In this paper, a multi-objective method is used to optimize a heat recovery steam generator (HRSG). Two objective functions have been used in the optimization, which are irreversibility and HRSG equivalent volume. The former expresses the exergetic efficiency and the latter demonstrates the cost of the HRSG. Decision variables are geometric and operational parameters of the HRSG. The result...

In this paper, a multi-objective method is used to optimize a heat recovery steam generator (HRSG). Two objective functions have been used in the optimization, which are irreversibility and HRSG equivalent volume. The former expresses the exergetic efficiency and the latter demonstrates the cost of the HRSG. Decision variables are geometric and operational parameters of the HRSG. The results of...

The increased competition in the domestic and international market has posed excessive pressure to the manufacturing organizations to successfully implement the ISO 9001 quality standards. The implementation process becomes more challenging when it is surrounded by numerous barriers. Though the presence of barriers makes it more difficult but certain factors (hereby known as enablers) makes it ...