Dynamic programming seeks to solve complex problems by breaking them down into multiple smaller problems. The solutions of these smaller problems are then combined to reach the overall solution. Deterministic algorithms have the advantage of accuracy but they need large computational power requirements. Heuristic algorithms have the advantage of speed but they provide less accuracy. This paper ...

In this paper, we consider heterogeneous distributed storage systems (DSSs) having flexible reconstruction degree, where each node in the system has dynamic repair bandwidth and dynamic storage capacity. In particular, a data collector can reconstruct the file at time t using some arbitrary nodes in the system and for an arbitrary node failure the system can be repaired by some set of arbitrary...

Recent studies in maritime shipping have concentrated on environmental and economic impacts of ships. In this regard, fuel is considered as one of the important factors for such impacts. In particular, the sailing speed of the vessels affects the fuel consumption directly. In this study, we consider a speed optimization problem in liner shipping, which is characterized by stochastic port times ...

Mathematical optimization is at the core of many problems in systems biology: (1) as the underlying hypothesis for model development, (2) in model identification, or (3) in the computation of optimal stimulation procedures to synthetically achieve a desired biological behavior. These problems are usually formulated as nonlinear programing problems (NLPs) with dynamic and algebraic constraints. ...

The charging method of lithium-ion batteries used in electric vehicles (EVs) significantly affects its commercial application. This paper aims to make three contributions to the existing literature. (1) In order to achieve an efficient charging strategy for lithium-ion batteries with shorter charging time and lower charring loss, the trade-off problem between charging loss and charging time has...