A Declarative Paradigm for Robust Cumulative Scheduling

Derrien, Alban; Petit, Thierry; Zampelli, Stéphane

doi:10.1007/978-3-319-10428-7_23

Cited by 4 publications

(8 citation statements)

References 11 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In this section we recall the conditions that are exploited by the algorithm. Proofs and explanations can be found in [3].…”

Section: Failure and Fix-point Conditionsmentioning

confidence: 99%

“…The Time-Table failure condition of FlexC integrates in the profile, at any time t, the maximum height among activities having a K-compulsory part intersecting t. Property 2 (FlexC (lower bounds) [3]). Given FlexC(A, C, K), the propagator should ensure ∀b ∈ A:…”

Section: Definition 2 (K-compulsory Part [3]mentioning

confidence: 99%

“…Property 3 (FlexC (upper bounds) [3]). Given FlexC(A, C, K), the propagator should ensure the same conditions as Property 2 with intervals [s b , e b [ (condition (1)) and…”

Section: Proposition 1 (Time-mentioning

confidence: 99%

“…To express this regret mechanism, we use a function max a (L), which returns the height of either the activity with maximum height if it is not a, or the second maximum otherwise. 3 Time complexity. Conversely to Sweep min, SKCP events in Sweep max can be created several times for a given activity a.…”

Section: Dynamic Versionmentioning

confidence: 99%

“…In this paper, we investigate the filtering algorithm of the FlexC constraint [3]. FlexC expresses cumulative problems that should integrate a given level of robustness.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Dynamic Sweep Filtering Algorithm for FlexC

Derrien¹,

Petit²,

Zampelli³

2014

Preprint

Self Cite

View full text Add to dashboard Cite

show abstract

“…In this section we recall the conditions that are exploited by the algorithm. Proofs and explanations can be found in [3].…”

Section: Failure and Fix-point Conditionsmentioning

confidence: 99%

Section: Definition 2 (K-compulsory Part [3]mentioning

confidence: 99%

“…Property 3 (FlexC (upper bounds) [3]). Given FlexC(A, C, K), the propagator should ensure the same conditions as Property 2 with intervals [s b , e b [ (condition (1)) and…”

Section: Proposition 1 (Time-mentioning

confidence: 99%

Section: Dynamic Versionmentioning

confidence: 99%

“…In this paper, we investigate the filtering algorithm of the FlexC constraint [3]. FlexC expresses cumulative problems that should integrate a given level of robustness.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Dynamic Sweep Filtering Algorithm for FlexC

Derrien¹,

Petit²,

Zampelli³

2014

Preprint

Self Cite

View full text Add to dashboard Cite

show abstract

Logic-Based Benders Decomposition for Super Solutions: An Application to the Kidney Exchange Problem

Chisca

Lombardi

Milano

et al. 2019

Lecture Notes in Computer Science

View full text Add to dashboard Cite

When optimising under uncertainty, it is desirable that solutions are robust to unexpected disruptions and changes. A possible formalisation of robustness is given by super solutions. An assignment to a set of decision variables is an (a, b, c) super solution if any change involving at most a variables can be repaired by changing at most b other variables; the repair solution should have a cost of at most c units worse than a non-robust optimum. We propose a method exploiting Logic Based Benders Decomposition to find super solutions to an optimisation problem for generic disruptions. The master deals with the original problem, while subproblems try to find repair solutions for each possible disruption. As a case study, we consider the Kidney Exchange Problem, for which our method scales dramatically better on realistic instances than a reformulationbased approach from the literature.

show abstract