We derive the first performance guarantees for a combinatorial online algorithm that schedules stochastic, nonpreemptive jobs on unrelated machines to minimize the expectation of the total weighted completion time. Prior work on unrelated machine scheduling with stochastic jobs was restricted to the offline case, and required sophisticated linear or convex programming relaxations for the assign...

This paper discusses an efficient heuristic to minimize the makespan of scheduling n independent jobs on m unrelated parallel machines. The problem of scheduling the jobs on the unrelated parallel machines is combinatorial in nature. Hence, the heuristic approach is inevitable for quicker solution. In this paper, a simple and efficient heuristic is designed to minimize the makespan of schedulin...

The unrelated parallel machine scheduling problem, in its most general form, is applicable to many manufacturing and service environments. This problem requires the scheduling of a group of independent jobs on unrelated parallel machines as well as the sequencing of the jobs on each individual machine. In this paper, we propose a genetic algorithm with adaptive crossover selection to schedule ...

In this paper we address a multi-objective scheduling problem for unrelated parallel machines. In unrelated parallel systems, the processing cost/time of a given job on different machines may vary. The objective of scheduling is to simultaneously determine the job-machine assignment and job sequencing on each machine. In such a way the total cost of the schedule is minimized. The cost function ...

This paper discusses design and comparison of Simulated Annealing Algorithm and Greedy Randomized Adaptive Search Procedure (GRASP) to minimize the makespan in scheduling n single operation independent jobs on m unrelated parallel machines. This problem of minimizing the makespan in single machine scheduling problem with uniform parallel machines is NP hard. Hence, heuristic development for suc...

We study a sequential version of the well-known KP-model: Each of n agents has a job that needs to be processed on any of m machines. Agents sequentially select a machine for processing their jobs. The goal of each agent is to minimize the finish time of his machine. We study the corresponding sequential price of anarchy for m identical machines under arbitrary and LPT orders, and suggest insig...

In this paper, we study a planning and scheduling problem for unrelated parallel machines. There are n jobs that have to be assigned and sequenced on m unrelated parallel machines. Each job has a weight that represents the priority of the corresponding customer order, a given due date, and a release date. An Automated Guided Vehicle is used to transport at maximum jobs into a storage space in f...

We derive a polynomial time approximation scheme for a special case of makespan minimization on unrelated machines. © 2009 Elsevier B.V. All rights reserved.