Models and Strategies for Variants of the Job Shop Scheduling Problem

Recently, a variety of constraint programming and Boolean satisfiability approaches to scheduling problems have been introduced. They have in common the use of relatively simple propagation mechanisms and an adaptive way to focus on the most constrained part of the problem. In some cases, these methods compare favorably to more classical constraint programming methods relying on propagation algorithms for global unary or cumulative resource constraints and dedicated search heuristics. In particular, we described an approach that combines restarting, with a generic adaptive heuristic and solution guided branching on a simple model based on a decomposition of disjunctive constraints. In this paper, we introduce an adaptation of this technique for an important subclass of job shop scheduling problems (JSPs), where the objective function involves minimization of earliness/tardiness costs. We further show that our technique can be improved by adding domain specific information for one variant of the JSP (involving time lag constraints). In particular we introduce a dedicated greedy heuristic, and an improved model for the case where the maximal time lag is 0 (also referred to as no-wait JSPs).Comment: Principles and Practice of Constraint Programming - CP 2011, Perugia : Italy (2011

Core-Guided and Core-Boosted Search for CP

Peer reviewe

Associations of lumbar scoliosis with presentation of suspected early axial spondyloarthritis

Objective: Scoliosis may impact the mechanical loading and cause secondary changes of the sacroiliac joints and lumbar spine. Our goal was to look how lumbar scoliosis modify the clinical and imaging-study in patients with recent-onset inflammatory back pain (IBP) suggesting axial spondyloarthritis (axSpA).Methods: Baseline weight-bearing lumbar-spine radiographs obtained in the DESIR cohort of patients aged 18-50 years and having IBP for at least 3 months but less than 3 years suggesting axSpA were studied. After training on scoliosis detection based on Cobb's angle>10 degrees plus Nash-Moe grade >= 1, readers blinded to patient data measured spine lumbar scoliosis, sacral horizontal angle, lumbosacral angle and lumbar lordosis on the radiograph of the lumbar and scored sacroiliitis on the radiograph of the pelvis. Baseline MRIs T1 and STIR of the lumbar spine and sacroiliac joints were evaluated for respectively degenerative changes and signs of axSpA.Results: Of the 360 patients (50.8% females) 88.7% had lumbar pain and 69.3% met ASAS criteria for axSpA. Mean Cobb's angle was 3.2 degrees +/- 5.0 degrees and 28 (7.7%) patients had lumbar scoliosis. No statistical differences were observed for radiographic sacroiliitis, MRI sacroiliitis, modified Stoke Ankylosing Spondylitis Spinal Score, Pfirmmann score, high-intensity zone, protrusion, extrusion, MODIC score between patients with and without scoliosis. In both groups, degenerative changes by MRI were rare and predominated at L4-L5 and L5-S1.Conclusion: In patients with early IBP suggesting axSpA, lumbar scoliosis was not associated with inflammatory or degenerative changes. (C) 2019 Elsevier Inc. All rights reserved.Imaging- and therapeutic targets in neoplastic and musculoskeletal inflammatory diseas

Metamorphic testing of constraint solvers

Constraint solvers are complex pieces of software and are notoriously difficult to debug. In large part this is due to the difficulty of pinpointing the source of an error in the vast searches these solvers perform, since the effect of an error may only come to light long after the error is made. In addition, an error does not necessarily lead to the wrong result, further complicating the debugging process. A major source of errors in a constraint solver is the complex constraint propagation algorithms that provide the inference that controls and directs the search. In this paper we show that metamorphic testing is a principled way to test constraint solvers by comparing two different implementations of the same constraint. Specifically, specialised propagators for the constraint are tested against the general purpose table constraint propagator. We report on metamorphic testing of the constraint solver Minion. We demonstrate that the metamorphic testing method is very effective for finding artificial bugs introduced by random code mutation

Propagating Dense Systems of Integer Linear Equations

ACM Symposium on Applied Computin

Propagating systems of dense linear integer constraints

C1 - Journal Articles Referee

Lazy Clause Generation: Combining the Power of SAT and CP (and MIP?) Solving

International Conference on Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems (CPAIOR