Solution approaches developed to date have not been efficient enough to handle realistically sized problems. The main approaches have been general integer programming algorithms and the specialized ...

It covers basic algorithm design techniques such as divide and conquer, dynamic programming, and greedy algorithms. It concludes with a brief introduction to intractability (NP-completeness) .

Daniel R. Jiang, Warren B. Powell, An Approximate Dynamic Programming Algorithm for Monotone Value Functions, Operations Research, Vol. 63, No. 6 (November-December 2015), pp. 1489-1511 ...

Dynamic programming (DP) algorithms have become indispensable in computational biology, addressing problems that range from sequence alignment and phylogenetic inference to RNA secondary structure ...

Coalition formation is one of the most studied topics in multi-agent systems. Central to this endeavor is the problem of partitioning the set of agents into exhaustive and disjoint coalitions so as to ...

The Dynamic Programming and Optimal Control class focuses on optimal path planning and solving optimal control problems for dynamic systems. It stands out for several reasons: It is multidisciplinary, ...

This study develops an advanced dynamic optimization model that leverages Mixed-Integer Linear Programming (MILP) alongside the Genetic Algorithm (GA) to tackle complex resource allocation and ...