Operations scheduling with multiple resources and transportation considerations

Abstract

We study a scheduling problem with the operations that require renewable as well as non-renewable resources. After an operation has been completed, the non-renewable resource is depleted whereas the renewable resource can be made available for the next operation. Of both the renewable and the non-renewable resources limited amounts are available and they need to be transported to the locations where they are needed. The operations have deadlines, and the availability of the renewable resources depends on the sequence of the operations. Such operations scheduling problems are commonly encountered in the practices of emergency logistics that deliver medical services to the affected areas after a disaster, where renewable resources typically refer to medical teams and non-renewable resources refer to medical supplies. We present a complexity classification for our problem and show where the borderline lies between NP-hardness and polynomial time solvability. We analyse the structural properties of our problem, provide strongly polynomial-time solutions for four special cases and list the cases that are computationally intractable. Finally, we propose a framework of heuristic procedures for solving more general versions of this problem.

Quantitative modeling in disaster management: A literature review

“…If resources have different capabilities or characteristics, then multiple units may need to collaborate to meet demand either by being scheduled sequentially or simultaneously. The relief scheduling literature [52,55,56,[58][59][60][61] addresses these interdependencies between resources.…”

“…can be made available again to meet additional demand. The models presented in [59][60][61] consider the efficient scheduling of both renewable and non-renewable resources. Bodaghi et al [59] introduce a biobjective optimization model to minimize the total weighted time of meeting demand as well as the overall makespan of the relief operation (i.e., the distribution of emergency resources to the affected areas).…”

“…Scheduling in [59] relies on coordinating the delivery sequence of renewable resources while dispatching non-renewable resources from distribution centers. The models developed in [60] and [61] consider coordinating the assignment and scheduling of non-renewable (medical and emergency supplies) and renewable (disaster medical assistance teams) resources with the objective of minimizing the total tardiness penalty across demand nodes. Lei et al [61] use a rolling-horizonbased greedy heuristic to determine how to allocate medical supplies from distribution centers to patients.…”

Multi-resource scheduling and routing for emergency recovery operations

“…Such delay and poor coordination could be avoided or minimised if scheduling of both expendable and non-expendable resources could be taken into consideration in the same optimisation process. However, scheduling problems for multiple resources during emergency situations have become more complicated than in the case of single resource scheduling [ 1 , 3 , 4 ]. The ERO will be more complex considering the fact that relief centre (RC) is usually subject to severe resource limitations and acute time pressures in deciding what resources are to be sent to which hospitals to rescue/save lives.…”

Investigations on Genetic Algorithm Performances in a Parallel Machines Scheduling Environment

“…The authors propose a metaheuristic based simulated annealing to minimize the makespan. Lee et al [18] investigate a scheduling problem in the practices of emergency logistics that deliver medical services to the affected areas after a disaster. They demonstrate that when the amount of consumable resource available at time zero is sufficient, then the problem becomes equivalent to a parallel machine scheduling problem with release dates and sequence dependent setup times; and as objective the total weighted tardiness.…”