TY - CHAP A1 - Borndörfer, Ralf A1 - Schenker, Sebastian A1 - Skutella, Martin A1 - Strunk, Timo ED - Greuel, G.-M. ED - Koch, Thorsten ED - Paule, Peter ED - Sommese, Andrew T1 - PolySCIP T2 - Mathematical Software – ICMS 2016, 5th International Conference, Berlin, Germany, July 11-14, 2016, Proceedings N2 - PolySCIP is a new solver for multi-criteria integer and multi-criteria linear programs handling an arbitrary number of objectives. It is available as an official part of the non-commercial constraint integer programming framework SCIP. It utilizes a lifted weight space approach to compute the set of supported extreme non-dominated points and unbounded non-dominated rays, respectively. The algorithmic approach can be summarized as follows: At the beginning an arbitrary non-dominated point is computed (or it is determined that there is none) and a weight space polyhedron created. In every next iteration a vertex of the weight space polyhedron is selected whose entries give rise to a single-objective optimization problem via a combination of the original objectives. If the ptimization of this single-objective problem yields a new non-dominated point, the weight space polyhedron is updated. Otherwise another vertex of the weight space polyhedron is investigated. The algorithm finishes when all vertices of the weight space polyhedron have been investigated. The file format of PolySCIP is based on the widely used MPS format and allows a simple generation of multi-criteria models via an algebraic modelling language. Y1 - 2016 SN - 978-3-319-42431-6 U6 - https://doi.org/10.1007/978-3-319-42432-3_32 VL - 9725 SP - 259 EP - 264 PB - Springer International Publishing ET - Mathematical Software – ICMS 2016 ER - TY - CHAP A1 - Scheumann, René A1 - Fügenschuh, Armin A1 - Schenker, Sebastian A1 - Vierhaus, Ingmar A1 - Borndörfer, Ralf A1 - Finkbeiner, Matthias ED - Seliger, Günther T1 - Global Manufacturing: How to Use Mathematical Optimisation Methods to Transform to Sustainable Value Creation BT - (GCSM 2012) T2 - Proceedings of the 10th Global Conference on Sustainable Manufacturing Y1 - 2012 SN - 978-605-63463-1-6 SP - 538 EP - 545 ER - TY - CHAP A1 - Schenker, Sebastian A1 - Vierhaus, Ingmar A1 - Borndörfer, Ralf A1 - Fügenschuh, Armin A1 - Skutella, Martin ED - Stark, Rainer ED - Seliger, Günther ED - Bonvoisin, Jérémy T1 - Optimisation Methods in Sustainable Manufacturing BT - Challenges, Solutions and Implementation Perspectives T2 - Sustainable Manufacturing N2 - Sustainable manufacturing is driven by the insight that the focus on the economic dimension in current businesses and lifestyles has to be broadened to cover all three pillars of sustainability: economic development, social development, and environmental protection. Y1 - 2017 SN - 978-3-319-48514-0 U6 - https://doi.org/10.1007/978-3-319-48514-0_15 SP - 239 EP - 253 PB - Springer International Publishing ER - TY - CHAP A1 - Buchert, Tom A1 - Neugebauer, Sabrina A1 - Schenker, Sebastian A1 - Lindow, Kai A1 - Stark, Rainer T1 - Multi-criteria Decision Making as a Tool for Sustainable Product Development - Benefits and Obstacles T2 - Procedia CIRP Y1 - 2015 U6 - https://doi.org/10.1016/j.procir.2014.07.110 VL - 26 SP - 70 EP - 75 ER - TY - CHAP A1 - Gausemeier, Pia A1 - Seliger, Günther A1 - Schenker, Sebastian A1 - Borndörfer, Ralf T1 - Nachhaltige Technologiepfade für unterschiedliche Entwicklungsniveaus mithilfe mehrkriterieller Entscheidungsfindung T2 - Vorausschau und Technologieplanung Y1 - 2014 SN - 978-3-942647-53-3 VL - 334 SP - 65 EP - 94 ER - TY - CHAP A1 - Sprösser, Gunther A1 - Schenker, Sebastian A1 - Pittner, Andreas A1 - Borndörfer, Ralf A1 - Rethmeier, Michael A1 - Chang, Ya-Ju A1 - Finkbeiner, Matthias T1 - Sustainable Welding Process Selection based on Weight Space Partitions T2 - Procedia CIRP Y1 - 2016 U6 - https://doi.org/10.1016/j.procir.2016.01.077 VL - 40 SP - 127 EP - 132 ER - TY - CHAP A1 - Schenker, Sebastian A1 - Steingrímsson, Jón Garðar A1 - Borndörfer, Ralf A1 - Seliger, Günther T1 - Modelling of Bicycle Manufacturing via Multi-criteria Mixed Integer Programming T2 - Procedia CIRP Y1 - 2015 U6 - https://doi.org/10.1016/j.procir.2014.07.068 VL - 26 SP - 276 EP - 280 ER - TY - GEN A1 - Schenker, Sebastian A1 - Borndörfer, Ralf A1 - Skutella, Martin T1 - A novel partitioning of the set of non-dominated points N2 - We consider a novel partitioning of the set of non-dominated points for general multi-objective integer programs with $k$ objectives. The set of non-dominated points is partitioned into a set of non-dominated points whose efficient solutions are also efficient for some restricted subproblem with one less objective; the second partition comprises the non-dominated points whose efficient solutions are inefficient for any of the restricted subproblems. We show that the first partition has the nice property that it yields finite rectangular boxes in which the points of the second partition are located. T3 - ZIB-Report - 16-55 Y1 - 2016 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-61286 SN - 1438-0064 ER - TY - GEN A1 - Scheumann, Rene A1 - Fügenschuh, Armin A1 - Schenker, Sebastian A1 - Vierhaus, Ingmar A1 - Borndörfer, Ralf A1 - Finkbeiner, Matthias T1 - Global Manufacturing: How to Use Mathematical Optimisation Methods to Transform to Sustainable Value Creation N2 - It is clear that a transformation to sustainable value creation is needed, because business as usual is not an option for preserving competitive advantages of leading industries. What does that mean? This contribution proposes possible approaches for a shift in existing manufacturing paradigms. In a first step, sustainability aspects from the German Sustainability Strategy and from the tools of life cycle sustainability assessment are chosen to match areas of a value creation process. Within these aspects are indicators, which can be measured within a manufacturing process. Once these data are obtained they can be used to set up a mathematical linear pulse model of manufacturing in order to analyse the evolution of the system over time, that is the transition process, by using a system dynamics approach. An increase of technology development by a factor of 2 leads to an increase of manufacturing but also to an increase of climate change. Compensation measures need to be taken. This can be done by e.g. taking money from the GDP (as an indicator of the aspect ``macroeconomic performance''). The value of the arc from that building block towards climate change must then be increased by a factor of 10. The choice of independent and representative indicators or aspects shall be validated and double-checked for their significance with the help of multi-criteria mixed-integer programming optimisation methods. T3 - ZIB-Report - 12-28 KW - Multi-Criteria Optimisation KW - Sustainability Indicator KW - System Dynamics KW - Value Creation Process Y1 - 2012 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-15703 SN - 1438-0064 ER - TY - GEN A1 - Maher, Stephen J. A1 - Fischer, Tobias A1 - Gally, Tristan A1 - Gamrath, Gerald A1 - Gleixner, Ambros A1 - Gottwald, Robert Lion A1 - Hendel, Gregor A1 - Koch, Thorsten A1 - Lübbecke, Marco A1 - Miltenberger, Matthias A1 - Müller, Benjamin A1 - Pfetsch, Marc A1 - Puchert, Christian A1 - Rehfeldt, Daniel A1 - Schenker, Sebastian A1 - Schwarz, Robert A1 - Serrano, Felipe A1 - Shinano, Yuji A1 - Weninger, Dieter A1 - Witt, Jonas T. A1 - Witzig, Jakob T1 - The SCIP Optimization Suite 4.0 N2 - The SCIP Optimization Suite is a powerful collection of optimization software that consists of the branch-cut-and-price framework and mixed-integer programming solver SCIP, the linear programming solver SoPlex, the modeling language Zimpl, the parallelization framework UG, and the generic branch-cut-and-price solver GCG. Additionally, it features the extensions SCIP-Jack for solving Steiner tree problems, PolySCIP for solving multi-objective problems, and SCIP-SDP for solving mixed-integer semidefinite programs. The SCIP Optimization Suite has been continuously developed and has now reached version 4.0. The goal of this report is to present the recent changes to the collection. We not only describe the theoretical basis, but focus on implementation aspects and their computational consequences. T3 - ZIB-Report - 17-12 Y1 - 2017 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-62170 SN - 1438-0064 ER - TY - GEN A1 - Gamrath, Gerald A1 - Fischer, Tobias A1 - Gally, Tristan A1 - Gleixner, Ambros A1 - Hendel, Gregor A1 - Koch, Thorsten A1 - Maher, Stephen J. A1 - Miltenberger, Matthias A1 - Müller, Benjamin A1 - Pfetsch, Marc A1 - Puchert, Christian A1 - Rehfeldt, Daniel A1 - Schenker, Sebastian A1 - Schwarz, Robert A1 - Serrano, Felipe A1 - Shinano, Yuji A1 - Vigerske, Stefan A1 - Weninger, Dieter A1 - Winkler, Michael A1 - Witt, Jonas T. A1 - Witzig, Jakob T1 - The SCIP Optimization Suite 3.2 N2 - The SCIP Optimization Suite is a software toolbox for generating and solving various classes of mathematical optimization problems. Its major components are the modeling language ZIMPL, the linear programming solver SoPlex, the constraint integer programming framework and mixed-integer linear and nonlinear programming solver SCIP, the UG framework for parallelization of branch-and-bound-based solvers, and the generic branch-cut-and-price solver GCG. It has been used in many applications from both academia and industry and is one of the leading non-commercial solvers. This paper highlights the new features of version 3.2 of the SCIP Optimization Suite. Version 3.2 was released in July 2015. This release comes with new presolving steps, primal heuristics, and branching rules within SCIP. In addition, version 3.2 includes a reoptimization feature and improved handling of quadratic constraints and special ordered sets. SoPlex can now solve LPs exactly over the rational number and performance improvements have been achieved by exploiting sparsity in more situations. UG has been tested successfully on 80,000 cores. A major new feature of UG is the functionality to parallelize a customized SCIP solver. GCG has been enhanced with a new separator, new primal heuristics, and improved column management. Finally, new and improved extensions of SCIP are presented, namely solvers for multi-criteria optimization, Steiner tree problems, and mixed-integer semidefinite programs. T3 - ZIB-Report - 15-60 KW - mixed-integer linear and nonlinear programming KW - MIP solver KW - MINLP solver KW - linear programming KW - LP solver KW - simplex method KW - modeling KW - parallel branch-and-bound KW - branch-cut-and-price framework KW - generic column generation KW - Steiner tree solver KW - multi-criteria optimization KW - mixed-integer semidefinite programming Y1 - 2016 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-57675 SN - 1438-0064 ER -