Answer Set Programming (ASP) has recently been employed to specify and run dynamic programming (DP) algorithms on tree decompositions, a central approach in the field of parameterized complexity, which aims at solving hard problems efficiently for instances of certain structure. This ASPbased method followed the standard DP approach where tables are computed in a bottom-up fashion, yielding goo...

Forming effective coalitions is a major research challenge in the field of multi-agent systems. Central to this endeavour is the problem of partitioning the set of agents into exhaustive and disjoint coalitions so as to maximize social welfare. This coalition structure generation problem is extremely challenging due to the exponential number of partitions that need to be examined. Specifically,...

High-level languages offer abstraction mechanisms that can reduce development time and improve software quality. But abstraction mechanisms often have an accumulative runtime overhead that can discourage their use. Multi-stage programming (MSP) languages offer constructs that make it possible to use abstraction mechanisms without paying a runtime overhead. This paper studies applying MSP to imp...

Stochastic network design techniques can be used effectively to solve a wide range of planning problems in ecological sustainability. We propose a novel approximate algorithm based on the sample average approximation (SAA) and mixed integer programming (MIP) to efficiently address the problem of using a limited budget to remove instream barriers, which prevent fish from accessing their natural ...

Pairwise ordered tree alignment is an important pattern matching problem, motivated by RNA secondary structure comparison for example, that can be solved efficiently using Dynamic Programming (DP). An inquiry into the multiplicity of optimal solutions, as well as the existence of potentially interesting sub-optimal solutions, naturally motivates the question of exploring the space of all, optim...

We consider a general class of dynamic programming (DP) problems with nonseparable objective functions. show that for any problem in this class, there exists an augmented-state DP satisfies the principle optimality and solutions to which yield original problem. Furthermore, we identify subclass naturally forward separable functions state-augmentation scheme is tractable. extend framework stocha...

Experimental data play an essential role in developing and refining models of physical systems. Not all experimental results are equally useful, and some experiments can be much more valuable than others. Well-chosen experiments can thus lead to substantial resource savings. Optimal experimental design seeks to quantify and maximize the value of experimental data. Common current practice for de...

Applications of dynamic programming (DP) algorithms are numerous, and include genetic engineering and operations research problems. At a high level, DP algorithms are specified as a system of recursive equations implemented using memoization. The recursive nature of these equations suggests that they can be written naturally in a functional language. However, the requirement for memoization pos...

We consider the revenue management problem of finding profit-maximizing prices for delivery time slots in context attended home delivery. This multistage optimal control admits a dynamic programming (DP) formulation that is intractable realistic sizes due to so-called “curse dimensionality.” therefore study three approximate DP algorithms both from numerical and control-theoretical perspective....

This paper addresses the problem of maximizing the power produced by an organic rankine cycle (ORC) waste heat recovery system on board a diesel-electric railcar. A simplified model of the system allows the formulation of an optimal control problem that can be solved via dynamic programming (DP). To increase the smoothness and the accuracy of the solution obtained offline using the implementati...