This paper deals with multi-period project portfolio selection problem. In this problem, the available budget is invested on the best portfolio of projects in each period such that the net profit is maximized. We also consider more realistic assumptions to cover wider range of applications than...

Extreme learning machine (ELM) allows for fast learning and better generalization performance than conventional gradient-based learning. However, the possible inclusion of non-optimal weight and bias due to random selection and the need for more hidden neurons adversely influence network...

The demand of energy is increasing at an escalating pace and cannot be fulfilled entirely by conventional energy systems, due to their limited supplies. In addition to this they have a radical impact on the environment. In comparison to them hybrid energy systems are a suitable combination of...

This paper proposes a penalty based differential evolution (P-DE) for extracting the parameters of solar photovoltaic (PV) modules at different environmental conditions. The two diode model of a solar cell is used as the basis for the extraction problem. The analyses carried out using synthetic...

Disasters are unforeseen occurrences requiring extensive transport deployment to support and relieve victims. Sometimes, this transportation is not feasible directly from some supply points to some destination points. Due to this tragedy, it is unclear precisely what is available at supply...

This paper deals with multi-period project portfolio selection problem. In this problem, the available budget is invested on the best portfolio of projects in each period such that the net profit is maximized. We also consider more realistic assumptions to cover wider range of applications than...