Master of Science / Department of Industrial & Manufacturing Systems Engineering / Todd W. Easton / Integer programs (IPs) are mathematical models that can provide organizations with the ability to optimally obtain their goals through appropriate utilization and allocation of available resources. Unfortunately, IPs are NP-complete in the strong sense, and many integer programs cannot be solved. Introduced by Gomory, lifting is a technique that takes a valid inequality and strengthens it. Lifting can result in facet defining inequalities, which are the theoretically strongest inequalities; because of this, lifting techniques are commonly used in commercial IP software to reduce the time required to solve an IP. This thesis introduces two new algorithms for exact simultaneous up lifting multiple sets into binary knapsack problems and introduces sequential simultaneous lifting. The Dynamic Programming Multiple Lifting Set Algorithm (DPMLSA) is a pseudopolynomial time algorithm bounded by O(nb) effort that can exactly uplift an arbitrary number of sets. The Three Set Simultaneous Lifting Algorithm (TSSLA) is a polynomial time algorithm bounded by O(n2) and can exact simultaneously up lift three sets. The simultaneously lifted inequalities generated by the DPMLSA and the TSSLA can be facet defining, and neither algorithm requires starting with a minimal cover. A brief computational study shows that the DPMLSA is fast and required an average of only 0.070 seconds. The computational study also shows these sequential simultaneously lifted inequalities are useful, as the solution time decreased by an overall average of 18.4%. Therefore, implementing the DPMLSA should be beneficial for large IPs.