In this paper, we propose an energy-efficient mathematical model for the resource-constrained project scheduling problem to optimize makespan and consumption of energy, simultaneously. In the proposed model, resources are speed-scaling machines. The problem is NP-hard in the strong sense. Therefore, a multi-objective fruit fly optimization algorithm (MOFOA) is developed. The MOFOA uses the VIKO...

To solve the clustering algorithm based on grid density on uncertain data stream in adjustment cycle for clustering omissions, the paper proposed an algorithm, named GCUDS, to cluster uncertain data steam using grid structure. The concept of the data trend degree was defined to describe the grade of a data point belonging to some grid unit and the defect of information loss around grid units wa...

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...

This paper presents a new approach to agglomerative hierarchical clustering. Classical hierarchical clustering algorithms are based on metrics which only consider the absolute distance between two clusters, merging the pair of clusters with highest absolute similarity. We propose a relative dissimilarity measure, which considers not only the distance between a pair of clusters, but also how dis...

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...

  This paper proposes two relax and fix heuristics for the simultaneous lot sizing and sequencing problem in permutation flow shops involving sequence-dependent setups and capacity constraints. To evaluate the effectiveness of mentioned heuristics, two lower bounds are developed and compared against the optimal solution. The results of heuristics are compared with the selected lower bound .

The use of Network Lifetime Maximization while disseminating queries to appropriate regions since data queries often include geographic attributes and apply Ant Colony Optimization clustering is proposed here. The protocol, uses energy aware and geographically-informed neighbor selection heuristics to route a packet towards the destination region to improve the link stability during data transf...

to identifying of the high yielding wheat lines with optimal characteristics and to determine the traits which could be used as the selection index for increasing of grain yield, 40 recombinant inbred lines derived from a cross between norstar and zagros cultivars were evaluated in a randomized complete block design with three replications. the measured characters consisted of peduncle weight, ...

As any other problem solving task that employs search, AI Planning needs heuristics to efficiently guide the problem-space exploration. Machine learning (ML) provides several techniques for automatically acquiring those heuristics. Usually, a planner solves a problem, and a ML technique generates knowledge from the search episode in terms of complete plans (macro-operators or cases), or heurist...