Learning and optimization are the two essential abilities of human beings for problem
solving. Similarly, computer scientists have made great efforts to design artificial neural …

In recent decades, the field of multiobjective optimization has attracted considerable interest
among evolutionary computation researchers. One of the main features that makes …

Multiobjective evolutionary algorithms (MOEAs) have proven their effectiveness and
efficiency in solving problems with two or three objectives. However, recent studies show …

The economy of scale provided by cloud attracts a growing number of organizations and
industrial companies to deploy their applications in cloud data centers (CDCs) and to …

Abstract Dynamic Multi-objective Optimization is a challenging research topic since the
objective functions, constraints, and problem parameters may change over time. Although …

In the last few decades, production and procurement of food grain in India have steadily
increased, however, storage capacity has not increased proportionally. The government of …

Highly scalable resource supply capacity of cloud computing has greatly improved the
execution speed of workflow applications, however, traditional workflow scheduling …

Energy efficient workflow scheduling is the demand of the present time's computing
platforms such as an infrastructure-as-a-service (IaaS) cloud. An appreciable amount of …

This research investigates the multi-period multi-modal bulk wheat transportation and
storage problem in a two-stage supply chain network of Public Distribution System (PDS) …

Abstract Multi-objective Evolutionary Algorithms (MOEAs) have proven their effectiveness
and efficiency in solving complex problems with two or three objectives. However, recent …