We present PICPA, a new algorithm for tackling constrained continuous multi-objective problems. The algorithm combines constraint propagation techniques and evolutionary concepts. Unlike other evolutionary algorithm which gives only heuristic solutions, PICPA is able to bound effectively the Pareto optimal front as well as to produce accurate approximate solutions.

In this paper, a many-objective optimization algorithm was developed using SPEA2 for system of four reservoirs in the Karun basin, including hydropower, municipal and industrial, agricultural, environmental objectives. For purpose, 53 years available data, hedging rules were two modes: with without applying fuzzy logic. used to optimize coefficients first 43 data last 10 test optimized rule cur...

As one of the most challenging combinatorial optimization problems in scheduling, the resource-constrained project scheduling problem (RCPSP) has attracted numerous scholars’ interest resulting in considerable research in the past few decades. However, most of these papers focused on the single objective RCPSP; only a few papers concentrated on the multi-objective resource-constrained project s...

The use of evolutionary algorithms (EAs) to solve problems with multiple objectives (known as Vector Optimization Problems (VOPs)) has attracted much attention recently. Being population based approaches, EAs offer a means to find a group of pareto–optimal solutions in a single run. Differential Evolution (DE) is an EA that was developed to handle optimization problems over continuous domains. ...

In the field of multiobjective optimization, important efforts have been made in recent years to generate global Pareto fronts uniformly distributed. A new multiobjective evolutionary algorithm, called ↗−MOGA, has been designed to converge towards ΘP , a reduced but well distributed representation of the Pareto set ΘP . The algorithm achieves good convergence and distribution of the Pareto fron...

We study the optimization of the spatial distribution of fuel injection rates in a gas turbine burner. An automated procedure is implemented for the optimization. The procedure entails an evolutionary optimization algorithm and an automated interface for the modification of the parameters in the experimental setup for the fuel injection and for the post-processing. The evolutionary algorithm is...

Article history: Received 5 June 2012 Received in revised form 12 June 2013 Accepted 19 November 2013 Available online 27 November 2013

This paper describes and demonstrates a new and highly innovative technique that identifies an approximation of the entire bounding surface of the feasible objective region directly, including deep concavities, disconnected regions and the edges of interior holes in the feasible areas. The Pareto front is a subset of the surface of the objective boundary and can be extracted easily. Importantly...

Although there are many versions of evolutionary algorithms that are tailored to multi–criteria optimization, theoretical results are apparently not yet available. Here, it is shown that results known from the theory of evolutionary algorithms in case of single criterion optimization do not carry over to the multi–criterion case. At first, three different step size rules are investigated numeri...