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...

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...

Machining operations are used for creating surfaces by cutting away unwanted materials from workpieces. These operations are highly constrained and non-linear in nature. As a result traditional techniques are not suitable for machining parameter optimisation. Turning and milling are the two most...

Logistics is no longer seen as tactical and cost-driven – it is strategic. Considering the driver-on-time rules and with the perishable nature of the products, the travel length/time is one of the critical constraints in distribution logistics. We consider a typical logistics problem with...

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...