Experimental analysis of dynamic minimum spanning tree algorithms
SODA '97 Proceedings of the eighth annual ACM-SIAM symposium on Discrete algorithms
Scheduling independent tasks to reduce mean finishing time
Communications of the ACM
Matchings in colored bipartite networks
Discrete Applied Mathematics
Two NP-Hardness Results for Preemptive Minsum Scheduling of Unrelated Parallel Machines
Proceedings of the 8th International IPCO Conference on Integer Programming and Combinatorial Optimization
The Constrained Minimum Spanning Tree Problem (Extended Abstract)
SWAT '96 Proceedings of the 5th Scandinavian Workshop on Algorithm Theory
Dynamic Graph Algorithms with Applications
SWAT '00 Proceedings of the 7th Scandinavian Workshop on Algorithm Theory
Reoptimization of minimum and maximum traveling salesman's tours
Journal of Discrete Algorithms
Reoptimizing the 0-1 knapsack problem
Discrete Applied Mathematics
Minimal cost reconfiguration of data placement in storage area network
WAOA'09 Proceedings of the 7th international conference on Approximation and Online Algorithms
A theory and algorithms for combinatorial reoptimization
LATIN'12 Proceedings of the 10th Latin American international conference on Theoretical Informatics
Some NP-complete problems in linear programming
Operations Research Letters
A new algorithm for reoptimizing shortest paths when the arc costs change
Operations Research Letters
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We consider reoptimization problems arising in production planning. Due to unexpected changes in the environment (out-of-order or new machines, modified jobs' processing requirements, etc.), the production schedule needs to be modified. That is, jobs might be migrated from their current machine to a different one. Migrations are associated with a cost --- due to relocation overhead and machine set-up times. The goal is to find a good modified schedule, which is as close as possible to the initial one. We consider the objective of minimizing the total flow time, denoted in standard scheduling notation by P ||∑Cj. We study two different problems: (i) achieving an optimal solution using the minimal possible transition cost, and (ii) achieving the best possible schedule using a given limited budget for the transition. We present optimal algorithms for the first problem and for several classes of instances for the second problem.