In a multiperiod dynamic network flow problem, we model uncertain arc capacities using scenario aggregation. This model is so large that it may be difficult to obtain optimal integer or even continuous solutions. We develop a Lagrangian decomposition method based on the structure recently introduced in [9]. Our algorithm produces a near-optimal primal integral solution and an optimum solution t...

task assignment problem (tap) involves assigning a number of tasks to a number of processors in distributed computing systems and its objective is to minimize the sum of the total execution and communication costs, subject to all of the resource constraints. tap is a combinatorial optimization problem and np-complete. this paper proposes a hybrid meta-heuristic algorithm for solving tap in a h...

Dealing with multi-objective combinatorial optimization and local search, this article proposes a new multi-objective meta-heuristic named Pareto Adaptive Decomposition algorithm (PAD). Combining ideas from decomposition methods, two phase algorithms and multi-armed bandit, PAD provides a 2-phase modular framework for finding an approximation of the Pareto front. The first phase decomposes the ...

The prediction of RNA secondary structure including pseudoknots remains a challenge due to the intractable computation of the sequence conformation from intriguing nucleotide interactions. Optimal algorithms often assume a restricted class for the predicted RNA structures and yet still require a high-degree polynomial time complexity, which is too expensive to use. Heuristic methods may yield t...

Transportation sector generates a considerable part of each nation's gross domestic product and considered among the largest consumers of oil products in the world. This paper proposes a heuristic method for the vehicle routing problem with hard time windows while incorporating the costs of fuel, driver, and vehicle. The proposed heuristic uses a novel speed optimization algorithm to reach its ...