Name
Abstract | ||
|---|---|---|
Crashing is shortening the project makespan by reducing activity times in a project network by allocating resources to them. Activity durations are often uncertain and an exact probability distribution itself might be ambiguous. We study a class of distributionally robust project crashing problems where the objective is to optimize the first two marginal moments (means and SDs) of the activity durations to minimize the worst-case expected makespan. Under partial correlation information and no correlation information, the problem is solvable in polynomial time as a semidefinite program and a second-order cone program, respectively. However, solving semidefinite programs is challenging for large project networks. We exploit the structure of the distributionally robust formulation to reformulate a convex-concave saddle point problem over the first two marginal moment variables and the arc criticality index variables. We then use a projection and contraction algorithm for monotone variational inequalities in conjunction with a gradient method to solve the saddle point problem enabling us to tackle large instances. Numerical results indicate that a manager who is faced with ambiguity in the distribution of activity durations has a greater incentive to invest resources in decreasing the variations rather than the means of the activity durations. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1002/net.21880 | NETWORKS |
Keywords | Field | DocType |
distributionally robust optimization,makespan,moments,project networks,projection and contraction algorithm,saddle point | Mathematical optimization,Saddle point,Job shop scheduling,Correlation,Mathematics,Project networks | Journal |
Volume | Issue | ISSN |
74.0 | 1.0 | 0028-3045 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Selin Damla Ahipaşaoğlu | 1 | 29 | 5.50 |
| Karthik Natarajan | 2 | 407 | 31.52 |
| Dongjian Shi | 3 | 4 | 1.10 |