implementation of the risk management concepts into construction practice may enhance the performance of project by taking appropriate response actions against identified risks. this research proposes a multi-criteria group decision making approach for the evaluation of different alternative response scenarios. to take into account the uncertainties inherent in evaluation process, fuzzy logic i...

Several problems in the area of financial optimization can be naturally dealt with optimization techniques under multiobjective approaches, followed by a decision-making procedure on the resulting efficient solutions. The problem of portfolio optimization is one of them. This chapter studies the use of evolutionary multiobjective techniques to solve such problems, focusing on Venezuelan market ...

Thfs paper briefly summarizes selected published results on the Surrogate Worth Trade-cf (SWT) yethod--a method for solving multiple objective optimization problems--andits exte-.;ions. The development of the SWT method is briefly discussed. Theoreticalbisis for the Kuhn-Tucker multipliers and trade-off functions associated with Paretooptimal solutions is presented. The SWT meth...

The Nurse Rostering Problem is an NP-hard combinatorial optimization, scheduling problem for assigning a set of nurses to shifts per day by considering both hard and soft constraints. A novel metaheuristic technique is required for solving Nurse Rostering Problem (NRP). This work proposes a metaheuristic technique called Directed Bee Colony Optimization Algorithm using the Modified Nelder-Mead ...

We address the no-wait k-stage flexible flowshop scheduling problem where there are m identical machines at each stage. The objectives are to schedule the available n jobs so that makespan and mean tardiness of n jobs are minimized. Sequence-dependent setup times are treated in this problem as one of the prominent practical assumptions. This problem is NP-hard, and therefore we present a new mu...

This paper presents a new multiobjective evolutionary algorithm for Environmental/Economic power Dispatch (EED) problem. The EED problem is formulated as a nonlinear constrained multiobjective optimization problem. A new Strength Pareto Evolutionary Algorithm (SPEA) based approach is proposed to handle the problem as a true multiobjective problem with competing and non-commensurable objectives....

In its current state, evolutionary multiobjective optimization (EMO) is an established field of research and application with more than 150 PhD theses, more than ten dedicated texts and edited books, commercial softwares and numerous freely downloadable codes, a biannual conference series running successfully since 2001, special sessions and workshops held at all major evolutionary computing co...

This paper models the process of a recommender system as a multiobjective optimization problem, a discrete particle swarm optimization framework is established and has been integrated into multiobjective optimization, consequently, a multiobjective discrete particle swarm optimization algorithm is proposed to solve the modeled optimization problem. Each run of the current mainstream recommender...

Algorithmic decision theory becomes more and more important. We will present a theoretical and practical point of view to the role of networks and dynamic flow problems in complex environments. To support a decision support management a comfortable software implementation for solving multiobjective discrete control and dynamic flow problems on networks will be presented. As many processes from ...