Many planning problems require maximizing the probability of goal satisfaction as well as minimizing the expected cost to reach the goal. To model and solve such problems, there have been several attempts at extending Stochastic Shortest Path problems (SSPs) to deal with dead ends and optimize a dual optimization criterion. Unfortunately these extensions lack either theoretical robustness or pr...

Deterministic engineering design often leads to unexpected or physically unrealizable results. This is due to the fact that deterministic design is not able to capture the effects of even slight natural fluctuations of parameters. Deterministic transonic shape optimization is no exception: deterministic designs can result in dramatically inferior performance when the actual operating conditions...

this paper explores the flexile flow lines where setup times are sequence- dependent. the optimization criterion is the minimization of total weighted completion time. we propose an iterated greedy algorithm (iga) to tackle the problem. an experimental evaluation is conducted to evaluate the proposed algorithm and, then, the obtained results of iga are compared against those of some other exist...

Due to the growing complexity of todays technical systems optimization is becoming an important issue within the design phase. The applicability of optimization algorithms in automatic design processes is strongly dependent on the stopping criterion. It is important that the optimum is reliably found but furthermore no time or computational resources should be wasted. Therefore a run time analy...

Large outliers break down linear and nonlinear regression models. Robust regression methods allow one to filter out the outliers when building a model. By replacing the traditional least squares criterion with the least trimmed squares criterion, in which half of data is treated as potential outliers, one can fit accurate regression models to strongly contaminated data. High-breakdown methods h...

In this paper, a particle swarm optimization algorithm (PSO) is presented to solve the permutaion flowshop sequencing problem (PFSP) with the objectives of minimizing makespan and maximum lateness of jobs, respectively. Simple but very efficient local search based on variable neighborhood search (VNS) is embedded in the particle swarm optimization algorithm to solve the well known benchmark sui...

In this paper, fast search algorithms are proposed and studied for vector quantization encoding using the K-dimensional (K-d) tree structure. Here, the emphasis is on the optimal design of the K-d tree for efficient nearest neighbor search in multidimensional space under a bucket-Voronoi intersection search framework. Efficient optimization criteria and procedures are proposed for designing the...

In this chapter, a heuristic perspective for the multiuser detection problem in the uplink of direct sequence code division multiple access (DS-CDMA) systems is discussed. In particular, the particle swarm optimization multiuser detector (PSO-MuD) is analyzed regarding several figures of merit, such as symbol error rate, near-far and channel error estimation robustness, and computational comple...

Decision making for complex systems is based on multi-criterion-optimization. A decision making support can be applied to find the Pareto solutions. Multi-criterion tabu programming is a new paradigm for that task. Similarly to rules applied in the genetic programming, tabu programming solves problems by using a tabu algorithm that modifies some computer programs. We consider the multi-criterio...