An Iterated Min–Max procedure for practical workload balancing on non-identical parallel machines in manufacturing systems

Best Effort Workload Disparity Minimization in Multi-Agent Systems With Capacity Constraints

“…Motivated by such an operational setting, several distributed load balancing approaches have been provided in the literature. Indicatively, in [19] a hierarchical approach that relies on the construction of virtual trees among the nodes in the network is provided; in [20] an algorithm is provided that balances the loads in spite of network unreliability; in [21] an algorithm is proposed to balance the loads of the base stations of a cellular network by suitably assigning the users; in [22] a noncooperative game theoretic approach was used to model and solve the load balancing problem and derive a distributed algorithm which provides a near-optimal solution; in [23], [24] noncooperative algorithms based on Wardrop equilibria and mean field game theory are developed; in [25] an algorithm is proposed for the workload balancing on non-identical parallel machines, based on a min-max optimization strategy. In [26], the problem is cast in the field of power dispatching.…”

Identical Parallel Machine Scheduling Considering Workload Smoothness Index

“…Calculate the difference between the maximum and the minimum workload, denoted Δ max For example, suppose there are seven jobs to be processed on two machines. The corresponding processing times of the jobs are (8,9,8,6,8,7,6). Let the maximum workload constraint be 29.…”

“…Large Job Instances (n ≥ 50) Below, we further test the performance of the proposed two heuristic algorithms together with the previous list scheduling algorithms with large job input instances. Especially, we consider two scenarios with regard to the variation range of the processing times of jobs, i.e., p j ∈ [5,10] or p j ∈ [8,10]. Similar to the case of small job input instances, three instances are generated for each combination (m, n), and the average results are reported in Tables 2 and 3, where the running time is in seconds.…”

“…Various optimization objectives, including the makespan and the total completion time, have been well addressed in previous studies [4][5][6][7]. In addition to the above classical objectives, workload balance between the machines together with the corresponding operators is also a major aspect of decision making in manufacturing industry [8][9][10]. It contributes to reducing the idleness and work-in-process and removing bottlenecks [8,11].…”

“…In addition to the above classical objectives, workload balance between the machines together with the corresponding operators is also a major aspect of decision making in manufacturing industry [8][9][10]. It contributes to reducing the idleness and work-in-process and removing bottlenecks [8,11]. Minimum imbalance is actually beneficial for minimizing the inventory of finished goods [12].…”