This paper proposes a novel hybrid t-way test generation strategy (where t indicates interaction strength), called High Level Hyper-Heuristic (HHH). HHH adopts Tabu Search as its high level meta-heuristic and leverages on the strength of four low level meta-heuristics, comprising of Teaching Learning based Optimization, Global Neighborhood Algorithm, Particle Swarm Optimization, and Cuckoo Sear...

Nowadays, with huge progress in digital imaging, new image processing methods are needed to manage digital images stored on disks. Image retrieval has been one of the most challengeable fields in digital image processing which means searching in a big database in order to represent similar images to the query image. Although many efficient researches have been performed for this topic so far, t...

Relevance feedback (RF) is an iterative process which refines the retrievals by utilizing user’s feedback marked on retrieved results. Recent research has focused on the optimization for RF heuristic selection. In this paper, we propose an automatic RF heuristic selection framework which automatically chooses the best RF heuristic for the given query. The proposed method performs two learning t...

Plugin-based software systems are the next step of evolution in application development. By supporting fine grained modularity not only on the source code but also on the post-compilation level, plugin frameworks help to handle complexity, simplify application configuration and deployment, and enable users or third parties to easily enhance existing applications with self-developed modules with...

In this paper, a brief summary of the heuristic methods, single-stage optimization methods, time-phased optimization methods, artificial intelligence (AI) techniques and iterative improvement methods are presented. Finally, some of the important characteristics of network programming methods and their strengths and weaknesses are identified and compared. Key-words Heuristic Methods, Single-Stag...

This paper analyzes the use of expert systems in production management and provides both an historical perspective and a review of some recently developed expert systems for production management problems. Current expert systems in production management fill two gaps associated with traditional optimization and heuristic methods. First, optimization and heuristic methods do not process semantic...

Optimization of machining processes is of primary importance for increasing machining efficiency and economics. Determining optimal values of machining parameters is performed by applying optimization algorithms to mathematical models of relationships between machining parameters and machining performance measures. In recent years, there has been an increasing trend of using empirical models an...

In this article, multiple-product PVRP with pickup and delivery that is used widely in goods distribution or other service companies, especially by railways, was introduced. A mathematical formulation was provided for this problem. Each product had a set of vehicles which could carry the product and pickup and delivery could simultaneously occur. To solve the problem, two meta-heuristic methods...

the determination of the ultimate pit limit (upl) is the first step in the open pit mine planning process. in this stage that parts of the mineral deposit that are economic to mine are determined. there are several mathematical, heuristic and meta-heuristic algorithms to determine upl. the optimization criterion in these algorithms is maximization of the total profit whilst satisfying the...