In many practical applications, the end-goal of multi-objective optimization is to select an implementable solution that close Pareto-optimal front while satisfying decision maker’s preferences. The making process challenging since it involves manual consideration all solutions. field multi-criteria offers methods help maker in this process. However, most only focus on analyzing solutions’ obje...

We propose a Mamdani-Type Fuzzy Inference based posterior decision-making approach to multi-objective diet optimization problem. optimize the problem with evolutionary algorithms that result in tens/hundreds of non-dominated solutions which is too large pick one them by decision-maker. Even though all are optimized for objectives simultaneously, not objective functions may be equally important ...

Abstract In many real-world scenarios, the utility of a user is derived from single execution policy. this case, to apply multi-objective reinforcement learning, expected returns must be optimised. Various scenarios exist where user’s preferences over objectives (also known as function) are unknown or difficult specify. such set optimal policies learned. However, settings maximised have been la...

Many real projects complete through the realization of one and only one path of various possible network paths. Here, these networks are called alternative stochastic networks (ASNs). It is supposed that the nodes of considered network are probabilistic with exclusive-or receiver and exclusive-or emitter. First, an analytical approach is proposed to simplify the structure of t...

Irrigation and fertilization of crops are common practices necessary for the viability of agricultural communities, but also responsible for water scarcity and water quality deterioration. The effort to cost-effectively manage fresh water availability and diffuse nutrient pollution at the same time needs to take into account trade-offs between economic and multiple environmental objectives. Agr...

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...