In the present research, a multi-objective model is proposed, which considers equity among the citizens in addition to the cost criterion. Then, the model will be solved using Reservation Level Tchebycheff Procedure (RLTP), which is one of the interactive multi-objective decision-making techniques. Subsequently, the obtained results will be compared with those of the single-objective models to ...

Ensemble methods are able to improve the predictive performance of many base classifiers. Up till now, they have been applied to classifiers that predict a single target attribute. Given the non-trivial interactions that may occur among the different targets in multi-objective prediction tasks, it is unclear whether ensemble methods also improve the performance in this setting. In this paper, w...

Decision making is hard. It often requires reasoning about uncertain environments, partial observability and action spaces that are too large to enumerate. In such tasks decisiontheoretic agents can often assist us. In most research on decision-theoretic agents, the desirability of actions and their effects is codified in a scalar reward function. However, many real-world decision problems have...

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...

We present new methodology based on Multi-Objective Markov Decision Processes for developing sequential decision support systems from data. Our approach uses sequential decision-making data to provide support that is useful to many different decision-makers, each with different, potentially time-varying preference. To accomplish this, we develop an extension of fitted-Q iteration for multiple o...

Establishing and maintaining protected areas (PAs) is a key action in delivering post-2020 biodiversity targets. PAs often need to meet multiple objectives, ranging from protection ecosystem service provision climate change mitigation, but available land conservation funding limited. Therefore, optimizing resources by selecting the most beneficial vital. Here, we advocate for flexible transpare...

When dealing with problems more than two objectives, sophisticated multi-objective optimization algorithms might be needed. Pareto optimization, which is based on the concept of dominated and non-dominated solutions, most widely utilized method when comparing solutions within a setting. However, in context where three or objectives are involved, effectiveness dominance approaches to drive conve...

In this research, the multi-objective project management decision problem with fuzzy goals and fuzzy constraints are considered. We constitute α-cut approach and two various fuzzy goal programming solution methods for solving the Multi-Objective Project Management (MOPM) decision problem under fuzzy environments. The Interactive fuzzy multi-objective linear programming (i-FMOLP) and Weighted Ad...