A novel hybrid method for tracking multiple indistinguishable maneuvering targets using a wireless sensor network is introduced in this paper. The problem of tracking the location of targets is formulated as a Maximum Likelihood Estimation. We propose a hybrid optimization method, which consists of an iterative and a heuristic search method, for finding the location of targets simultaneously. T...

This paper discusses the problem of placing weighted items in a circular container in two-dimensional space. This problem is of great practical significance in various mechanical engineering domains, such as the design of communication satellites. Two constructive heuristics are proposed, one for packing circular items and the other for packing rectangular items. These work by first optimizing ...

Resource constrained project scheduling problem (RCPSP) is mainly investigated with the objective of either minimizing project makespan or maximizing project net present value. However, when material planning plays a key role in a project, the existing models cannot help determining material ordering plans to minimize material costs. In this paper, the RCPSP incorporated with the material order...

In this paper, a novel global optimization approach in the form of an adaptive hyper-heuristic, namely HyperDE, is proposed. As naming suggests, method based on Differential Evolution (DE) heuristic, which well-established inspired by theory evolution. Additionally, two other similar approaches are introduced for comparison and validation, HyperSSA HyperBES, Sparrow Search Algorithm (SSA) Bald ...

The most recent approaches of multi-objective optimization constitute application of meta-heuristic algorithms for which, parameter tuning is still a challenge. The present work hybridizes swarm intelligence with fuzzy operators to extend crisp values of the main control parameters into especial fuzzy sets that are constructed based on a number of prescribed facts. Such parameter-less particle ...

The number of heuristic optimization algorithms has exploded over the last decade with new methods being proposed constantly. A recent overview of existing heuristic methods has listed over 130 algorithms. The majority of these optimization algorithms have been designed and applied to solve real-parameter function optimization problems, each claiming to be superior to other methods in terms of ...

In this paper several probabilistic search techniques are developed for global optimization under three heuristic classi"cations: simulated annealing, clustering methods and adaptive partitioning algorithms. The algorithms proposed here combine di!erent methods found in the literature and they are compared with well-established approaches in the corresponding areas. Computational results are ob...

Response surface methodology is a common tool in optimizing processes. It mainly concerns situations when there is only one response of interest. However, many designed experiments often involve simultaneous optimization of several quality characteristics. This is called a Multiresponse Surface Optimization problem. A common approach in dealing with these problems is to apply desirability funct...

A novel optimization algorithm named teaching-learning-based optimization (TLBO) algorithm and its implementation procedure were presented in this paper. TLBO is a meta-heuristic method, which simulates the phenomenon in classes. TLBO has two phases: teacher phase and learner phase. Students learn from teachers in teacher phases and obtain knowledge by mutual learning in learner phase. The suit...