We solve the problem of robot path planning using Dynamic Programming (DP) designed to perform well in case of a sudden path blockage. A conventional DP algorithm works well for real time scenarios only when the update frequency is high i.e. changes can be readily propagated. In case updates are costly, for a sudden blockage the robot continues moving along the wrong path or stands stationary. ...

Recent improvements in vehicle-to-everything (V2X) communication and onboard computing power have enabled the development of control algorithms that jointly optimize vehicle velocity powertrain Connected Automated Vehicles (CAVs), commonly referred to as Eco-Driving problem. This paper presents a novel computationally efficient algorithm planning energy management CAV with hybrid electric power...

For the problem of long video transmission delay and low network efficiency caused by high energy consumption, a Dynamic Programming & Markov Decision Processes (DP-MDP) video transmission scheme is proposed. This scheme takes advantage of that the user instant request is independent to the past states. We combine the DP algorithm with MDP to solve relative problem in the user request process, ...

We present a new Dynamic Programming (DP) formulation of the Coalition Structure Generation (CSG) problem based on imposing a hierarchical organizational structure over the agents. We show the efficiency of this formulation by deriving DyPE, a new optimal DP algorithm which significantly outperforms current DP approaches in speed and memory usage. In the classic case, in which all coalitions ar...

Reinforcement Learning methods based on approximating dynamic programming (DP) are receiving increased attention due to their utility in forming reactive control policies for systems embedded in dynamic environments. Environments are usually modeled as controlled Markov processes, but when the environment model is not known a priori, adaptive methods are necessary. Adaptive control methods are ...

We formulate the ‘backpacker problem’ as an extension of the binary knapsack problem, and present two dynamic programming (DP) algorithms to solve this problem to optimality. Firstly, we propose a DP algorithm that solves the problem in pseudo polynomial time. Based on the observation that the optimal objective function is a step function of the knapsack capacity, we present an improved, ‘shift...

In this paper is developed an optimal control of fermentation process of L-lysine production with the Neuro-dynamic programming theory. A approximation neural network is developed and the decision of the optimization problem is improved by an iteration mode founded on the Bellman equation. With this optimization procedure the quantity L-lysine productions is increased at the end of the process....

We present a linear mixed integer programming model for the time-dependent heterogeneous green vehicle routing and scheduling problem (GVRSP) with the objective of minimizing total carbon dioxide emissions and weighted tardiness. Instead of discrete time intervals, the proposed model takes the traveled distances of arcs in different time periods as decision variables to determine the travel sch...

The emergence of budget airlines, the advent of new sales channels, the disappearance of traditional fare-class fences, and other on-going changes in the airline industry pose serious challenges to traditional revenue management models, which make some rigid and unrealistic assumptions. One of these is that passengers who do not get the fare they want book and travel on other airlines or do not...

In this paper, we describe a fast search algorithm for statistical translation based on dynamic programming (DP) and present experimental results. The approach is based on the assumption that the word alignment is monotone with respect to the word order in both languages. To reduce the search eeort for this approach, we introduce two methods: an acceleration technique to eeciently compute the d...