Designing difficult office space allocation problem instances with mathematical programming

Office space allocation (OSA) refers to the assignment of room space to a set of entities (people, machines, roles, etc.), with the goal of optimising the space utilisation while satisfying a set of additional constraints. In this paper, a mathematical programming approach is developed to model and generate test instances for this difficult and important combinatorial optimisation problem. Systematic experimentation is then carried out to study the difficulty of the generated test instances when the parameters for adjusting space misuse (overuse and underuse) and constraint violations are subject to variation. The results show that the difficulty of solving OSA problem instances can be greatly affected by the value of these parameters

Office space allocation by using mathematical programming and meta-heuristics

Office Space Allocation (OSA) is the task of efficient usage of spatial resources of an organisation. A common goal in a typical OSA problem is to minimise the wastage of space either by limiting the overuse or underuse of the facilities. The problem also contains a myriad of hard and soft constraints based on the preferences of respective organisations. In this thesis, the OSA variant usually encountered in academic institutions is investigated. Previous research in this area is rather sparse. This thesis provides a definition, extension, and literature review for the problem as well as a new parametrised data instance generator. In this thesis, two main algorithmic approaches for tackling the OSA are proposed: The first one is integer linear programming. Based on the definition of several constraints and some additional variables, two different mathematical models are proposed. These two models are not strictly alternatives to each other. While one of them provides more performance for the types of instances it is applicable, it lacks generality. The other approach provides less performance; however, it is easier to apply this model to different OSA problems. The second algorithmic approach is based on metaheuristics. A three step process in heuristic development is followed. In the first step, general local search techniques (descent methods, threshold acceptance, simulated annealing, great deluge) traverse within the neighbourhood via random relocation and swap moves. The second step of heuristic development aims to investigate large sections of the whole neighbourhood greedily via very fast cost calculation, cost update, and search for best move procedures within an evolutionary local search framework. The final step involves refinements and hybridisation of best performing (in terms of solution quality) mathematical programming and meta-heuristic techniques developed in prior steps. This thesis aims to be one of the pioneering works in the research area of OSA. The major contributions are: the analysis of the problem, a new parametrised data instance generator, mathematical programming models, and meta-heuristic approaches in order to extend the state-of-the art in this area

Office space allocation by using mathematical programming and meta-heuristics

Office Space Allocation (OSA) is the task of efficient usage of spatial resources of an organisation. A common goal in a typical OSA problem is to minimise the wastage of space either by limiting the overuse or underuse of the facilities. The problem also contains a myriad of hard and soft constraints based on the preferences of respective organisations. In this thesis, the OSA variant usually encountered in academic institutions is investigated. Previous research in this area is rather sparse. This thesis provides a definition, extension, and literature review for the problem as well as a new parametrised data instance generator. In this thesis, two main algorithmic approaches for tackling the OSA are proposed: The first one is integer linear programming. Based on the definition of several constraints and some additional variables, two different mathematical models are proposed. These two models are not strictly alternatives to each other. While one of them provides more performance for the types of instances it is applicable, it lacks generality. The other approach provides less performance; however, it is easier to apply this model to different OSA problems. The second algorithmic approach is based on metaheuristics. A three step process in heuristic development is followed. In the first step, general local search techniques (descent methods, threshold acceptance, simulated annealing, great deluge) traverse within the neighbourhood via random relocation and swap moves. The second step of heuristic development aims to investigate large sections of the whole neighbourhood greedily via very fast cost calculation, cost update, and search for best move procedures within an evolutionary local search framework. The final step involves refinements and hybridisation of best performing (in terms of solution quality) mathematical programming and meta-heuristic techniques developed in prior steps. This thesis aims to be one of the pioneering works in the research area of OSA. The major contributions are: the analysis of the problem, a new parametrised data instance generator, mathematical programming models, and meta-heuristic approaches in order to extend the state-of-the art in this area

Effect of Densification Temperature and Some Surfacing Techniques on the Surface Roughness of Densified Scots Pine (Pinus sylvestris L.)

WOS: 000331996500018The effects of densification temperature, planing, circular sawing, and sanding on the surface roughness of densified Scots pine using the open-system thermodynamic method were studied. Densification was applied to Scots pine at 6 MPa pressure and at temperatures of 120 degrees C, 140 degrees C, and 160 degrees C. A total of 1040 specimens (160 x 50 x 10 mm) were prepared using the surfacing techniques of planing, circular sawing, and sanding. The surface roughness of the specimens were measured in conformance with the TS 2495, EN ISO 3274, and the TS 6212 EN ISO 4288 standards, and the results were subjected to statistical analysis. The surface roughness of the planed surfaces was 26% lower, of the surfaces cut circularly was 38% lower, and of the sanded surfaces was 32% lower in densified Scots pine compared to undensified Scots pine. According to the densification temperature, while the lowest roughness was obtained in the densified specimens at 140 degrees C, raising the temperature to 160 degrees C increased the roughness. An increase in the number of blades in planing, the tooth number in circular sawing, and the grit number in planing decreased the surface roughness. Furthermore, the roughness was less in tangential surfaces compared to radial surfaces

Evaluation of antioxidant enzyme levels as biological markers at different stages of pneumoconiosis in coal workers

45th Congress of the European-Societies-of-Toxicology -- OCT 05-08, 2008 -- Rhodes, GREECEWOS: 000259252100711European Soc Toxico

Relationship of inflammatory cytokines with disease severity in CWP patients

45th Congress of the European-Societies-of-Toxicology -- OCT 05-08, 2008 -- Rhodes, GREECEWOS: 000259252100693European Soc Toxico

Visual clarity of irrigants used during flexible ureterorenoscopy: an in vitro comparison

WOS:000615231400016PubMed: 33552578Introduction Saline solution is the standard irrigant used during ureteroscopy. However, there is an opinion that water has better visual clarity. We aimed to compare the visual clarities of saline, water, and 5% mannitol as an irrigant during ureteroscopy. Material and methods An in vitro model consisting of an irrigant-filled container and a fiberoptic flexible ureteroscope was designed. A 1951 USAF Resolution Test Target and color checker within irrigants were used to evaluate the clarity of vision. The visual clarity was compared for 0.9% saline, distilled water and 5% mannitol solution with screen resolution and color contrast. The tests were repeated after adding human blood (2/400 ml) and contrast (20/400 ml) to the irrigants. Results There was no significant difference in resolution values of three plain irrigants at a distance of 10 mm. However, when blood was added to the irrigants, a better resolution of 29.3% for water and 20.6% for mannitol was achieved compared to saline. At 20 mm of distance, it was observed that the difference was more pronounced in irrigants with blood. Water and mannitol had 55.6% and 37.1% better resolution than saline, respectively. in the color reproduction test, there was no significant difference in the three plain irrigants, however, water had better color contrast compared to the others. Conclusions Water and 5% mannitol did not provide a significant image clarity advantage compared to saline. However, when blood was added to the irrigants, water provided significantly better visual clarity compared to saline. The use of water during various clinical scenarios in flexible ureteroscopy should be further investigated

Malignant transformation arising from mature cystic teratoma of the ovary: A report of six cases

Aim: Malignant transformation of mature cystic teratoma (MCT) is an uncommon complication. Preoperative diagnosis is difficult because of the lack of specific symptoms and signs indicating malignancy. Thus, we retrospectively analyzed the clinical characteristics of patients and the role of surgery in their management