We investigate the computability of problems in probabilistic planning and partially observable innnite-horizon Markov decision processes. The undecidability of the string-existence problem for probabilistic nite automata is adapted to show that the following problem of plan existence in probabilistic planning is undecidable: given a probabilistic planning problem, determine whether there exist...

Planning in large partially observable Markov decision processes (POMDPs) is challenging especially when a long planning horizon is required. A few recent algorithms successfully tackle this case but at the expense of a weaker information-gathering capacity. In this paper, we propose Information Gathering and Reward Exploitation of Subgoals (IGRES), a randomized POMDP planning algorithm that le...

Aggregate production planning (APP) determines the optimal production plan for the medium term planning horizon. The purpose of the APP is effective utilization of existing capacities through facing the fluctuations in demand. Recently, fuzzy approaches have been applied for APP focusing on vague nature of cost parameters. Considering the importance of coping with customer demand in different p...

Graph planning gives rise to fundamental algorithmic questions such as shortest path, traveling salesman problem, etc. A classical problem in discrete planning is to consider a weighted graph and construct a path that maximizes the sum of weights for a given time horizon T . However, in many scenarios, the time horizon is not fixed, but the stopping time is chosen according to some distribution...

We repeat Case Study 1 (see Section 4.3) for different planning horizons. In particular, in Case Study 1 we considered a planning horizon of 6 months (primarily because of data availability). To study the effect of the length of the planning horizon, we present here results for planning horizons of 3 months and 4.5 months. Table 3 reports the weights that our methodology assigns to each of the ...

Article history: Received 12 August 2012 Received in revised form 10 June 2013 Accepted 16 August 2013 Available online 13 September 2013 An action case study demonstrates an effective integration of collaborative planning using long-range foresight in a hierarchical government research organization. The purpose of the study was to evaluate the effectiveness of collaborative, bottom-up strategi...

Mobile robots are envisioned to cooperate closely with humans and to integrate seamlessly into a shared environment. For locomotion, these environments resemble traversable areas which are shared between multiple agents like humans and robots. The seamless integration of mobile robots into these environments requires accurate predictions of human locomotion. This work considers optimal control ...

In this paper, production planning and scheduling problems are addressed through a hierarchical framework. The planning problem aggregates orders in the planning period and considers uncertainty utilizing a multi-stage stochastic programming formulation where three stages are considered with increasing level of uncertainty. The planning model includes material balances and time horizon constrai...

In this paper, a multi-period and multi-resource operating room (OR) scheduling and rescheduling problem with elective and semi-elective (semi-urgent) patients is addressed. A scheduling-rescheduling framework based on the so-called rolling horizon approach is proposed to solve the problem. The core of the proposed framework is a novel proposed mixed-integer linear programming (MILP) model with...