A multi-start iterated tabu search algorithm for the multi-resource agent bottleneck generalized assignment problem

Abstract

In this study, a multi-resource agent bottleneck generalized assignment problem (MRBGAP) is addressed. In the bottleneck generalized assignment problem (BGAP), more than one job can be assigned to an agent, and the objective function is to minimize the maximum load over all agents. In this problem, multiple resources are considered and the capacity of the agents is dependent on these resources and it has minimum two indices. In addition, agent qualifications are taken into account. In other words, not every job can be assignable to every agent. The problem is defined by considering the problem of assigning jobs to employees in a firm. BGAP has been shown to be NP- hard. Consequently, a multi-start iterated tabu search (MITS) algorithm has been proposed for the solution of large-scale problems. The results of the proposed algorithm are compared by the results of the tabu search (TS) algorithm and mixed integer linear programming (MILP) model.

A comprehensive modeling approach for the task mapping problem in heterogeneous systems with dataflow processing units

“…As such the definition is closely related to the agent bottleneck generalized assignment problem in the field of production research. 13,14 In both problem formulations, the parallel execution through different agents is central, but communication cost and interdependencies between the tasks (agents) are not present. A recent publication by Alasmar et al bases its work on a similar model, labeling the problem as workload distribution.…”

“…The task‐device execution times are given through a utilization matrix. As such the definition is closely related to the agent bottleneck generalized assignment problem in the field of production research 13,14 . In both problem formulations, the parallel execution through different agents is central, but communication cost and interdependencies between the tasks (agents) are not present.…”