In this paper, we consider the problem of scheduling on two-machine permutation flowshop with minimal time lags between consecutive operations of each job. The aim is to find a feasible schedule that minimizes the total tardiness. This problem is known to be NP-hard in the strong sense. We propose two mixed-integer linear programming (MILP) models and two types of valid inequalities which aim t...

Hundreds of genes, when manipulated, affect the lifespan of model organisms (yeast, worm, fruit fly, and mouse) and thus can be defined as longevity-associated genes (LAGs). A major challenge is to determine whether these LAGs are model-specific or may play a universal role as longevity regulators across diverse taxa. A wide-scale comparative analysis of the 1805 known LAGs across 205 species r...

Nigeria’s over-dependence on crude oil revenue has exposed the economy to price shocks emanating from vicissitudes in global market, which accentuated need for urgent economic diversification. One of such areas that holds potential diversification is solid mineral subsector. The study examined influence development growth Nigeria, using Auto Regressive Distributed Lag (ARDL) Approach. Time seri...

The main objective of this study gears towards evaluating monetary policy transmission paths and money supply in Sub- Saharan Africa: evidence from Nigeria Ghana from1981- 2018. Central Bank Nigeria, World Bank, Development Indicator 2018 furnished us with the data used for analysis. This explored three different channels: interest rate, credit asset pricing channels these variables were regres...

This paper investigates the determinants of current account deficit in Sierra Leone, within framework Auto Regressive Distributed Lag (ARDL) bound testing approach with annual time series data from 1980 to 2020. The unit root results reveal that variables constitute both I(0) and I(1) series, while test confirms existence cointegration. confirm budget deficit, external debt real exchange rate a...

Learning from data means a process of information extraction from finite size samples in order to estimate an unknown dependency. A series of problems can be modeled in terms of a system that computes according to an unknown rule a response (output) for each input. The paper provides a series of results concerning the learning from data a linear regressive model in a multivariate framework. The...

This study investigates the impact of energy consumption and financial development on economic growth using neo-classical production function in the case of US. The ARDL (Autoregressive distributed lag) bounds testing approach with additional variables (energy consumption and financial development) is used to investigate cointegration during the period of 1967-2012 in US. The ARDL reveals a coi...