Assembly sequence planning (ASP) plays an important role in intelligent manufacturing. As ASP is a non-deterministic polynomial (NP) hard problem, it is scarcely possible for a brute force approach to find out the optimal solution. Therefore, increasing meta-heuristic algorithms are introduced to solve the ASP problem. However, due to the discreteness and strong constraints of ASP problem, most...

Many optimisation problems are dynamic in the sense that changes occur during the optimisation process, and therefore are more challenging than the stationary problems. To solve dynamic optimisation problems, the proposed approaches should not only attempt to seek the global optima but be able to also keep track of changes in the track record of landscape solutions. In this research work, one o...

Article history: Received: 18.03.2016. Received in revised form: 05.06.2016. Accepted: 07.06.2016. Transformers are crucial components in power systems. Due to market globalization, power transformer manufacturers are facing an increasingly competitive environment that mandates the adoption of design strategies yielding better performance at lower mass and losses. Multi-objective Optimization P...

Optimized utilization of resources is the need of the hour in any manufacturing system. A properly planned schedule is often required to facilitate optimization. This makes scheduling a significant phase in any manufacturing scenario. The Job Shop Scheduling Problem is an operation sequencing problem on multiple machines with some operation and machine precedence constraints, aimed to find the ...

Naturally occurring phenomenon serves as an unbiased guide for solving various optimization problems. This paper compiles some of the population-based, stochastic optimization algorithms including the recently developed social impact theory based optimizer, SITO. The current state of research, including the natural phenomena followed by each and some of their applications to solve various optim...

This paper addresses the application of Self-adaptive Global Best Harmony Search (SGHS) algorithm for the supervised training of feed-forward neural networks (NNs). A structure suitable to data representation of NNs is adapted to SGHS algorithm. The technique is empirically tested and verified by training NNs on two classification benchmarking problems. Overall training time, sum of squared err...

A new metaheuristic method applied to the global path planning for mobile robots in dynamic environments is presented. This algorithm, named the Quad Harmony Search method, consists of dividing the robot‟s environment into free regions by applying the Quad-tree algorithm and utilizing this information to accelerate the next phase which implements the Harmony Search optimization method to provid...

Many methods have been developed for structural size and configuration optimization in which cross-sectional areas are usually assumed to be continuous. In most practical structural engineering design problems, however, the design variables are discrete. This paper proposes two efficient structural optimization methods based on the harmony search (HS) heuristic algorithm that treat both discret...

Harmony search (HS) is a meta-heuristic algorithm mimicking the improvisation process of musicians. This paper arranges the basic structure of the HS algorithm and customizes the algorithm for clustering optimization problems. We propose novel clustering algorithm based on Harmony Search (HS) optimization method that deals with document clustering. By modeling Retrieval as an optimization probl...