Distributed Domain Propagation

Portfolio parallelization is an approach that runs several solver instances in parallel and terminates when one of them succeeds in solving the problem. Despite its simplicity, portfolio parallelization has been shown to perform well for modern mixed-integer programming (MIP) and boolean satisfiability problem (SAT) solvers. Domain propagation has also been shown to be a simple technique in modern MIP and SAT solvers that effectively finds additional domain reductions after the domain of a variable has been reduced. In this paper we introduce distributed domain propagation, a technique that shares bound tightenings across solvers to trigger further domain propagations. We investigate its impact in modern MIP solvers that employ portfolio parallelization. Computational experiments were conducted for two implementations of this parallelization approach. While both share global variable bounds and solutions, they communicate differently. In one implementation the communication is performed only at designated points in the solving process and in the other it is performed completely asynchronously. Computational experiments show a positive performance impact of communicating global variable bounds and provide valuable insights in communication strategies for parallel solvers

Utilization of glucose recovered by phase separation system from acid-hydrolysed oil palm empty fruit bunch for bioethanol production

Oil palm empty fruit bunch (OPEFB) is one the most abundant lignocellulosic wastes produced throughoutthe year in the palm oil industry. A new process of separating lignocellulose components after acid hydrolysis(known as phase separation system) has been previously developed, by which lignin and carbohydrate can becompletely and rapidly separated in 60 minutes between 25 and 30°C. In this process, cellulose is completelyhydrolyzed to oligosaccharides and remains in the acid phase. The maximum glucose yield of 53.8% wasobtained by hydrolysis, with 4% acid after autoclaving at 121°C for 5 minutes. This work focused on theseparation of monosaccharide (glucose) from cellulose fraction, which was subsequently used as a substratefor ethanol production. For this purpose, different types of nitrogen sources were evaluated, with yeast extractas the best nitrogen source (93% of theoretical yield) as compared to palm oil mill effluent (POME) andsludge powder for the growth of acid tolerant Saccharomyces cerevisiae ATCC 26602. Batch and repeatedbatch fermentation of S. cerevisiae ATCC 26602 using OPEFB hydrolysate gave 0.46 g glucose g ethanol-1,representing 87% of theoretical yield with a productivity of about 0.82 g-1 l-1 h-1 and 0.48 g glucose g ethanol-1,representing 89% of theoretical yield with productivity of about 2.79 g-1 l-1 h-1, respectively

Distributed Domain Propagation

This is the final version. Available on open access from the publisher via the DOI in this record16th International Symposium on Experimental Algorithms (SEA 2017), 21-23 June 2017, London, UKPortfolio parallelization is an approach that runs several solver instances in parallel and terminates when one of them succeeds in solving the problem. Despite it’s simplicity portfolio parallelization has been shown to perform well for modern mixed-integer programming (MIP) and boolean satisfiability problem (SAT) solvers. Domain propagation has also been shown to be a simple technique in modern MIP and SAT solvers that effectively finds additional domain reductions after a variables domain has been reduced. This paper investigates the impact of distributed domain propagation in modern MIP solvers that employ portfolio parallelization. Computational experiments were conducted for two implementations of this parallelization approach. While both share global variable bounds and solutions they communicate differently. In one implementation the communication is performed only at designated points in the solving process and in the other it is performed completely asynchronously. Computational experiments show a positive performance impact of communicating global variable bounds and provide valuable insights in communication strategies for parallel solvers.German Federal Ministry of Education and Researc

UG Framework to Parallelize MIP, MINLP, and ExactIP Solvers

Open House, ISM in Tachikawa, 2012.6.15統計数理研究所オープンハウス（立川）、H24.6.15ポスター発

SCIP-Jack—a solver for STP and variants with parallelization extensions

This is the author accepted manuscript. The final version is available from Springer Verlag via the DOI in this record The Steiner tree problem in graphs is a classical problem that commonly arises in practical applications as one of many variants. While often a strong relationship between different Steiner tree problem variants can be observed, solution approaches employed so far have been prevalently problemspecific. In contrast, this paper introduces a general-purpose solver that can be used to solve both the classical Steiner tree problem and many of its variants without modification. This versatility is achieved by transforming various problem variants into a general form and solving them by using a state-ofthe-art MIP-framework. The result is a high-performance solver that can be employed in massively parallel environments and is capable of solving previously unsolved instances.German Federal Ministry of Education and Researc

An Exceptionally Difficult Binary Quadratic Optimization Problem with Symmetry: a Challenge for The Largest Unsolved QAP Instance Tai256c

Tai256c is the largest unsolved quadratic assignment problem (QAP) instance in QAPLIB. It is known that QAP tai256c can be converted into a 256 dimensional binary quadratic optimization problem (BQOP) with a single cardinality constraint which requires the sum of the binary variables to be 92. As the BQOP is much simpler than the original QAP, the conversion increases the possibility to solve the QAP. Solving exactly the BQOP, however, is still very difficult. Indeed, a 1.48\% gap remains between the best known upper bound (UB) and lower bound (LB) of the unknown optimal value. This paper shows that the BQOP admits a nontrivial symmetry, a property that makes the BQOP very hard to solve. The symmetry induces equivalent subproblems in branch and bound (BB) methods. To effectively improve the LB, we propose an efficient BB method that incorporates a doubly nonnegative relaxation, the standard orbit branching and a technique to prune equivalent subproblems. With this BB method, a new LB with 1.25\% gap is successfully obtained, and computing an LB with $1.0\%$ gap is shown to be still quite difficult.Comment: 19 pages, 7 figures. arXiv admin note: substantial text overlap with arXiv:2210.1596

Corporate R&D Activities and Public Funding in Science, Technology, and Innovation

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