Journal ArticleDOI
A survey of algorithms for single and multi-objective unrelated parallel-machine deterministic scheduling problems
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This survey reveals that while makespan minimization has been fairly widely studied, problems that include processing characteristics such as release times, sequence dependent setups, and preemptions remain largely unstudied.Abstract:
This paper surveys the literature related to solving traditional unrelated parallel-machine scheduling problems. It compiles algorithms for the makespan, total weighted sum of completion times, maximum tardiness, total tardiness, total earliness and tardiness, and multiple criteria performance measures. The review of the existing algorithms is restricted to the deterministic problems without setups, preemptions, or side conditions on the problem. Even for such traditional problems, this survey reveals that while makespan minimization has been fairly widely studied, problems that include processing characteristics such as release times, sequence dependent setups, and preemptions remain largely unstudied. Research in solving unrelated parallel-machine scheduling problems involving the minimization of the number of tardy jobs, weighted number of tardy jobs, total tardiness, and total weighted tardiness is quite limited.read more
Citations
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Parallel machine scheduling with additional resources: Notation, classification, models and solution methods
TL;DR: This paper presents a review and discussion of studies on the parallel machine scheduling problems with additional resources, and extensions of integer programming models for two main classes of related problems are given.
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Heuristics for minimizing regular performance measures in unrelated parallel machine scheduling problems
TL;DR: Computational results show that the proposed metaheuristic outperforms other existing heuristics for each of the three objectives when run with a parameter setting appropriate for the objective.
Journal ArticleDOI
Genetic algorithm-based subproblem solution procedures for a modified shifting bottleneck heuristic for complex job shops
TL;DR: It turns out that using near to optimal sub problem solution procedures leads in many situations to improved results compared to dispatching-based subproblem solution procedures.
Journal ArticleDOI
A particle swarm optimization for a fuzzy multi-objective unrelated parallel machines scheduling problem
TL;DR: An effective multi-objective particle swarm optimization (MOPSO) algorithm to find a good approximation of Pareto frontier where total weighted flow time, total weighted tardiness, and total machine load variation are to be minimized simultaneously.
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Scheduling identical parallel machines to minimize total tardiness
TL;DR: This paper develops and evaluates an efficient heuristic algorithms for finding optimal or near-optimal schedules for the identical parallel-machine problem to minimize total tardiness.
References
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Book
Scheduling: Theory, Algorithms, and Systems
TL;DR: Scheduling will serve as an essential reference for professionals working on scheduling problems in manufacturing and computing environments and Graduate students in operations management, operations research, industrial engineering and computer science will find the book to be an accessible and invaluable resource.
Journal ArticleDOI
Approximation algorithms for scheduling unrelated parallel machines
TL;DR: It is proved that no polynomial algorithm can achieve a worst-case ratio less than 3/2 unlessP = NP, and a complexity classification for all special cases with a fixed number of processing times is obtained.
Journal ArticleDOI
Heuristic Algorithms for Scheduling Independent Tasks on Nonidentical Processors
Oscar H. Ibarra,Chul E. Kim +1 more
TL;DR: A simplified scheduling problem involving identical processors and restricted task sets is shown to be P-complete, however, the LPT algorithm applied to this problem yields schedules which are near optimal for large n .