Dynamic mapping (matching and scheduling) heuristics for a class of independent tasks using heterogeneous distributed computing systems are studied. Two types of mapping heuristics are considered: on-line and batch mode heuristics. Three new heuristics, one for batch and two for on-line, are introduced as part of this research. Simulation studies are performed to compare these heuristics with s...

In this paper, a hub covering location problem is considered. Hubs, which are the most congested part of a network, are modeled as M/M/C queuing system and located in placeswhere the entrance flows are more than a predetermined value.A fuzzy constraint is considered in order to limit the transportation time between all origin-destination pairs in the network.On modeling, a nonlinear mathematica...

One of the key elements in production planning hierarchy is master production scheduling. The aim of this study is to evaluate and compare thirteen alternative MPS development methods, including multi-objective optimization as well as twelve heuristics, in different operating conditions for multi-product single-level capacity-constrained production systems. We extract six critical criteria from...

Dynamic mapping (matching and scheduling) heuristics for a class of independent tasks using heterogeneous distributed computing systems are studied. Two types of mapping heuristics are considered: immediate mode and batch mode heuristics. Three new heuristics, one for batch mode and two for immediate mode, are introduced as part of this research. Simulation studies are performed to compare thes...

Admissible heuristics are critical for effective domainindependent planning when optimal solutions must be guaranteed. Two useful heuristics are the h heuristics, which generalize the reachability heuristic underlying the planning graph, and pattern database heuristics. These heuristics, however, have serious limitations: reachability heuristics capture only the cost of critical paths in a rela...

Hyper-heuristics are (meta-)heuristics that operate at a high level to choose or generate a set of low-level (meta-)heuristics to solve difficult search and optimisation problems. Evolutionary algorithms are well-known natureinspired meta-heuristics that simulate Darwinian evolution. In this article, we introduce an evolutionary-based hyper-heuristic in which a set of low-level heuristics compe...

In this paper, we adapted and expanded a set of guidelines, also known as heuristics, to evaluate the usability of software to now be appropriate for software aimed at children with autism spectrum disorder (ASD). We started from the heuristics developed by Nielsen in 1990 and developed a modified set of 15 heuristics. The first 5 heuristics of this set are the same as those of the original Nie...

In the field of heuristic search it is well-known that improving the quality of an admissible heuristic can significantly decrease the search effort required to find an optimal solution. Existing literature often assumes that admissible heuristics are consistent, implying that consistency is a desirable attribute. To the contrary, this paper shows that an inconsistent heuristic can be preferabl...

We exhibit a large class of simple rules of behavior, which we call adaptive heuristics, and show that they generate rational behavior in the long run. These adaptive heuristics are based on natural regret measures, and may be viewed as a bridge between rational and behavioral viewpoints. Taken together, the results presented here establish a solid connection between the dynamic approach of ada...

The constraint satisfaction community has developed a number of heuristics for variable ordering during backtracking search. For example, in conjunction with algorithms which check forwards, the Fail-First (FF) and Brelaz (Bz) heuristics are cheap to evaluate and are generally considered to be very eeective. Recent work to understand phase transitions in NP-complete problem classes enables us t...