We present a new mechanism to introduce diversity into two multiobjective approaches based on ant colony optimisation and randomised greedy algorithms to solve a more realistic extension of a classical industrial problem: time and space assembly line balancing. Promising results are shown after applying the designed constructive metaheuristics to ten real-like problem instances.

In view of the fact that enterprises can improve productivity through workflows, problem huge number multi-user workflows and unbalanced user load on cloud computing platforms is investigated, based an ant colony algorithm for decision task optimisation. With help a intelligence algorithm, automatic scheduling tasks optimisation resources are accomplished while satisfying enterprise's needs, me...

Ant colony optimisation techniques are usually guided by pheromone and heuristic cost information when choosing the next element to add to a solution. However, while an individual element may be attractive, usually its long term consequences are neither known nor considered. For instance, a short link in a TSP may be incorporated into an ant’s solution, yet, as a consequence of this link, the r...

Processing the excessive volumes of information on the Web is an important issue. The Semantic Web paradigm has been proposed as the solution. However, this approach generates several challenges, such as query processing and optimisation. This paper proposes a novel approach for optimising SPARQL queries with different graph shapes. This new method reorders the triple patterns using Ant Colony ...

Ant-based algorithms simulate the cooperative behaviour of real ants in finding food resources. A significant number of studies have focused on the self-organised behaviour of ants in the natural environment to develop effective systems for dynamic problems. Ant-based systems have special properties such as scalability, adaptability, and dynamicity, which are the main requirements for solving v...

many real world problems can be modelled as an optimization problem. evolutionary algorithms are used to solve these problems. ant colony algorithm is a class of evolutionary algorithms that have been inspired of some specific ants looking for food in the nature. these ants leave trail pheromone on the ground to mark good ways that can be followed by other members of the group. ant colony optim...

In this paper we present the implementation of a concurrent ant colony optimisation based solver for the combinatorial Single Machine Total Weighted Tardiness Problem (ACOSMTWTP). We introduce S-Net, a coordination language based on dataflow principles, report on the performance of the implementation and compare it against a sequential and a parallel implementation of the same algorithm in C. A...