Shahriar Asta

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In this study a novel memory based particle swarm optimization algorithm is presented. This algorithm utilizes external memory. A set of globally found best and worst positions, along with their parameters are stored in two separate external memories. At each iteration, a coefficient, based on the distance of the current particle to the closest best and(More)
Multi-mode resource and precedence-constrained project scheduling is a well-known challenging real-world optimisation problem. An important variant of the problem requires scheduling of activities for multiple projects considering availability of local and global resources while respecting a range of constraints. This problem has been addressed by a(More)
This paper deals with the application of modern software development tools on simulation development. Recently, Agile Software Development (ASD) methods enjoy an increasing popularity. eXtreme Programming (XP) techniques, one of the techniques which belong to the ASD group of methods is a software development method which improves software quality and(More)
Hyper-heuristics have emerged as automated high level search methodologies that manage a set of low level heuristics for solving computationally hard problems. A generic selection hyper-heuristic combines heuristic selection and move acceptance methods under an iterative single point-based search framework. At each step, the solution in hand is modified(More)
An apprenticeship-learning-based technique is used as a hyperheuristic to generate heuristics for an online combinatorial problem. It observes and learns from the actions of a known-expert heuristic on small instances, but has the advantage of producing a general heuristic that works well on other larger instances. Specifically, we generate heuristic(More)
Gesticulation is an essential component of face-to-face communication, and it contributes significantly to the natural and affective perception of human-to-human communication. In this work we investigate a new multimodal analysis framework to model relationships between intonational and gesture phrases using the hidden semi-Markov models (HSMMs). The HSMM(More)
A common form of a hyper-heuristic is a method that controls a search process which uses neighbourhood operators. There have many studies showing that hyper-heuristics are reusable for solving unseen problem instances not only from a particular domain but also different problem domains without requiring any change. However, generally hyper-heuristics have(More)
In online bin-packing problems, a policy must be found for assigning items, according their size, immediately upon their arrival to bins with known initial capacities. In previous work of Ozcan and Parkes (GECCO 2011), a policy was represented as a 2-dimensional "matrix" (array) and good matrices were then evolved using a genetic algorithm (GA). Here, we(More)
Biped locomotion for humanoid robots is a challenging problem that has come into prominence in recent years. As the degrees of freedom of a humanoid robot approaches to that of humans, the need for a better, flexible and robust maneuverability becomes inevitable for real or realistic environments. This paper presents new motion types for a humanoid robot in(More)