Using quadratic programming to solve high multiplicity scheduling problems on parallel machines
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Publication:675305
DOI10.1007/BF02522821zbMath0865.68008OpenAlexW2075392870MaRDI QIDQ675305
Publication date: 30 June 1997
Published in: Algorithmica (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/bf02522821
Related Items (4)
Quadratic M-convex and L-convex functions ⋮ Parallel approximation to high multiplicity scheduling problemsVIAsmooth multi-valued quadratic programming ⋮ Using quadratic programming to solve high multiplicity scheduling problems on parallel machines ⋮ Two simulated annealing-based heuristics for the job shop scheduling problem
Cites Work
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- Using quadratic programming to solve high multiplicity scheduling problems on parallel machines
- An O(n) algorithm for quadratic knapsack problems
- An algorithm for a singly constrained class of quadratic programs subject upper and lower bounds
- A polynomial algorithm for an integer quadratic non-separable transportation problem
- On polynomial solvability of the high multiplicity total weighted tardiness problem
- A strongly polynomial algorithm for minimum convex separable quadratic cost flow problems on two-terminal series-parallel networks
- Solving integer minimum cost flows with separable convex cost objective polynomially
- An $O(EV\log V)$ Algorithm for Finding a Maximal Weighted Matching in General Graphs
- Strongly Polynomial Algorithms for the High Multiplicity Scheduling Problem
- Scheduling independent tasks to reduce mean finishing time
- Technical Note—Minimizing Average Flow Time with Parallel Machines
- Convex separable optimization is not much harder than linear optimization
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