Adaptive sample size and sampling intervals schemes have been widely used to improve the statistical efficiency of Hotelling T² control chart in detecting small changes when the quality of a product or a process can be characterised by the multivariate distribution of quality characteristics....

The flexible job-shop scheduling problem (FJSP) is one of the most complex problems (Meriem and Ghédira, 2004). Thus, exact methods are not effective for solving the FJSP and heuristic approaches are generally used to find near optimal solutions within reasonable computation times. In our...

This paper aims to minimise the makespan of a set of identical batch processing machines in parallel. The batch processing machine can process a batch of jobs as long as the total size of all the jobs in the batch does not exceed its capacity. The processing time of the job and its size are...

This paper presents a new statistics-based evolutionary algorithm to improve the qualities of power supplies, in which operational costs and the stability of the power supply are optimised to provide a highly smooth but low-cost power supply service to customers. The proposed method is...

The present paper introduces a new clonal particle swarm optimisation (CPSO) and PSO techniques to develop efficient adaptive forecasting models for short and long-term prediction of S&P 500 and DJIA stock indices. The basic structure of the models is an adaptive linear combiner whose weights...

The main objective of any supply chain is to satisfy its customers by supplying goods and services at the right time, the right place, the right quantity and the right quality, which determines the productivity. This age of globalisation has made the pressure more intense for supply chains. In...

This article presents how genetic algorithm (GA) can be efficiently used to fuzzy goal programming (FGP) formulation of quadratic bilevel programming problems (QBLPPs) in a hierarchical decision system. In the proposed approach, the concept of tolerance membership functions in fuzzy sets for...

Hybridisation of algorithms to develop efficient solution methods for solving various NP-hard problems has been a practice for the last few years. It can be seen that researchers have tried different permutations and combinations of various exact, heuristic and metaheuristic algorithms to...

As globalisation and international sourcing prevail, constructing an optimal combination of diverse suppliers has become of great importance for meeting measurable objectives, such as on-time delivery, cost efficiency and risk mitigation. This paper presents a method for solving a sealed-bid,...

In this paper, a novel hybrid intelligent framework is developed by applying a systematic integration of group method of data handling (GMDH) neural networks with genetic algorithm and rule-based expert system with web-based text mining for crude oil price forecasting. Our research reveals that...