Formulating the single machine sequencing problem with release dates as a mixed integer program
Discrete Applied Mathematics - Southampton conference on combinatorial optimization, April 1987
Single-machine scheduling polyhedra with precedence constraints
Mathematics of Operations Research
A time indexed formulation of non-preemptive single machine scheduling problems
Mathematical Programming: Series A and B
Structure of a simple scheduling polyhedron
Mathematical Programming: Series A and B
Integer Programming Formulation of Traveling Salesman Problems
Journal of the ACM (JACM)
Scheduling Jobs of Equal Length: Complexity, Facets and Computational Results
Proceedings of the 4th International IPCO Conference on Integer Programming and Combinatorial Optimization
Parallel Machine Scheduling by Column Generation
Operations Research
Solving Parallel Machine Scheduling Problems by Column Generation
INFORMS Journal on Computing
Time-Indexed Formulations for Machine Scheduling Problems: Column Generation
INFORMS Journal on Computing
Parallel machine scheduling through column generation: minimax objective functions
ESA'06 Proceedings of the 14th conference on Annual European Symposium - Volume 14
Mixed integer programming formulations for single machine scheduling problems
Computers and Industrial Engineering
Improvements and extensions to the Miller-Tucker-Zemlin subtour elimination constraints
Operations Research Letters
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Mixed integer programming (MIP) formulations for scheduling problems can be classified based on the decision variables upon which they rely. In this paper, four different MIP formulations based on four different types of decision variables are presented for various parallel machine scheduling problems. The goal of this research is to identify promising optimization formulation paradigms that can subsequently be used to either (1) solve larger practical scheduling problems of interest to optimality and/or (2) be used to establish tighter lower solution bounds for those under study. We present the computational results and discuss formulation efficacy for total weighted completion time and maximum completion time problems for the identical parallel machine case.