A Heuristic Algorithm for Multi-layer Network Optimization in Cloud Computing
One of the most important concepts in cloud computing is modeling the problem as a multi-layer optimization problem which leads to cost savings in designing and operating the networks. Previous researchers have modeled the two-layer network operating problem as an Integer Linear Programming (ILP) problem, and due to the computational complexity of solving it jointly, they suggested a two-stage procedure for solving it by considering one layer at each stage.
In this paper, considering the ILP model and using some properties of it, we propose a heuristic algorithm for solving the model jointly, considering unicast, multicast, and anycast flows simultaneously.
We first sort demands in decreasing order and use a greedy method to realize demands in order. Due to the high computational complexity of ILP model, the proposed heuristic algorithm is suitable for networks with a large number of nodes; In this regard, various examples are solved by CPLEX and MATLAB soft wares.
Our simulation results show that for small values of M and N CPLEX fails to find the optimal solution, while AGA finds a near-optimal solution quickly.
The proposed greedy algorithm could solve the large-scale networks approximately in polynomial time and its approximation is reasonable.
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Pricing in a dual channel closed-loop supply chain: A game theory approach
Maryam Almasi, *
Iranian Journal Of Operations Research, Summer and Autumn 2023