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...

We consider the problem of scheduling a number of jobs on a number of unrelated parallel machines in order to minimize the makespan. We develop three heuristic approaches, i.e., a genetic algorithm, a tabu search algorithm and a hybridization of these heuristics with a truncated branch-and-bound procedure. This hybridization is made in order to accelerate the search process to near-optimal solu...

The problem addressed in this paper is scheduling jobs on unrelated parallel machines with sequence-dependent setup times to minimize the maximum completion time (i.e., the makespan). This problem is NP-hard even without including setup times. Adding sequence-dependent setup times adds another dimension of complexity to the problem and obtaining optimal solutions becomes very difficult especial...

The paper presents a priority rule-based heuristic serial schedule (SS) algorithm for a deterministic scheduling problem where multiple jobs with arbitrary precedence constraints are processed on multiple unrelated parallel machines. The objective is to minimise makespan. The priority rule employs the arithmetic mean and deviation of the processing times to determine the prior job-machine pair....

This article deals with a quite complex machine scheduling problem comprising the following features: 1. unrelated parallel machines; 2. jobs have different due dates; 3. job splitting is allowed; 4. setup times are sequence dependent; 5. the objective function is to minimize the weighted sum of early, tardy and setup costs. The problem is formulated as a mixed-integer programming model which i...

The research proposes a two-phase matching-based decoding scheme that will be incorporated into bi-objective simulated annealing (SA) to solve unrelated parallel machine scheduling problems (UPMSP). The two objectives are to maximize the satisfactions of makespan and average tardiness, in terms of fuzzy measure. The effectiveness of the decoding scheme is investigated using four simulated annea...

The work addresses the NP-hard problem of scheduling a set of jobs to unrelated parallel machines with the overall objective of minimizing makespan. The solution presented proposes a greedy constructive algorithm followed by an application of a Variable Neighborhood Decent strategy that continually improves the incumbent solution until a local optimum is reached. The strength of the approach li...

We consider the problem of scheduling jobs that arrive online in the unrelated machine model to minimize `k norms of weighted flowtime. In the unrelated setting, the processing time and weight of a job depends on the machine it is assigned to, and it is perhaps the most general machine model considered in scheduling literature. Chadha et al. [10] obtained a recent breakthrough result in obtaini...

Parallel-machine scheduling research is one of the active fields in the past decade due to its increasing application. Due to the problem complexity, it is a general practice to find an appropriate heuristic rather than an optimal solution for the parallel-machine scheduling problem. The wirebonding workstation is the bottleneck in integrated-circuit packaging manufacturing. Effective schedulin...