Constrained partially observable Markov decision processes (CPOMDPs) have been used to model various real-world phenomena. However, they are notoriously difficult solve optimality, and there exist only a few approximation methods for obtaining high-quality solutions. In this study, grid-based approximations in combination with linear programming (LP) models generate approximate policies CPOMDPs...

General Optimization Methods Mathematical Programming, Constraint Programming, Heuristics Problem Specific Algorithms (Dynamic Programming, Branch and Bound) Scheduling Single and Parallel Machine Models Flow Shops and Flexible Flow Shops Job Shops Resource-Constrained Project Scheduling Timetabling Interval Scheduling, Reservations Educational Timetabling Workforce and Employee Timetabling Tra...

The purpose of the paper is to introduce a new type of fuzzy matrix games: fuzzy constrained matrix games. A computational method for its solution based on establishment of the auxiliary fuzzy linear programming for each player is proposed. The approach based on the multiobjective programming is established to solve these fuzzy linear programming. Effectiveness is illustrated with a numerical e...

This paper studies constrained portfolio problems that may involve constraints on the probability or the expected size of a shortfall of wealth or consumption. Our first contribution is that we solve the problems by dynamic programming, which is in contrast to the existing literature that applies the martingale method. More precisely, we construct the non-separable value function by formalizing...

This paper studies constrained portfolio problems that may involve constraints on the probability or the expected size of a shortfall of wealth or consumption. Our first contribution is that we solve the problems by dynamic programming, which is in contrast to the existing literature that applies the martingale method. More precisely, we construct the non-separable value function by formalizing...