Many practical chemical engineering problems involve the determination of optimal trajectories given multiple and conflicting objectives. These conflicting objectives typically give rise to a set of Pareto optimal solutions. To enhance real-time decision making efficient approaches are required for determining the Pareto set in a fast and accurate way. Hereto, the current paper illustrates the ...

This paper presents a multi-objective optimal power flow technique using particle swarm optimization. Two conflicting objectives, generation cost, and environmental pollution are minimized simultaneously. A multiobjective particle swarm optimization method is used to solve this highly nonlinear and non-convex optimization problem. A diversity preserving technique is incorporated to generate eve...

When an individual’s preferences depend on the time or ‘frame’ at which decisions are made, the preferences that appear at different frames must be aggregated in order to make social decisions. Suppose we aggregate each individual i’s frame-based preferences with a ‘behavioral welfare relation’ that ranks x above y if, when both x and y are available, i sometimes choose x and not y and never ch...

The Pareto front reflects the optimal trade-offs between conflicting objectives and can be used to quantify the effect of different beam configurations on plan robustness and dose-volume histogram parameters. Therefore, our aim was to develop and implement a method to automatically approach the Pareto front in robust intensity-modulated proton therapy (IMPT) planning. Additionally, clinically r...

Commercial plant breeders improve economically important traits by selectively mating individuals from a given breeding population. Potential pairings are evaluated before the growing season using Monte Carlo simulation, and a mating design is created to allocate a fixed breeding budget across the parent pairs to achieve desired population outcomes. We introduce a novel objective function for t...

A novel approach of differential evolution (DE) by incorporating the Pareto-optimal set is presented for optimising train movement through tuning fuzzy membership functions in mass transit systems. The Pareto-optimal based multiobjective optimisation approach uniquely provides a set of optimal non-dominated solutions to the decision-maker. From the set, the decision-maker selects satisfactory s...

Optimizing gate scheduling at airports is an old, but also a broad problem. The main purpose of this problem is to find an assignment for the flights arriving at and departing from an airport, while satisfying a set of constraints.A closer look at the literature in this research line shows thatin almost all studies airport gate processing time has been considered as a fix parameter. In this res...