TY - JOUR A1 - Hosoda, Junko A1 - Maher, Stephen J. A1 - Shinano, Yuji A1 - Villumsen, Jonas Christoffer T1 - A parallel branch-and-bound heuristic for the integrated long-haul and local vehicle routing problem on an adaptive transportation network JF - Computers & Operations Research N2 - Consolidation of commodities and coordination of vehicle routes are fundamental features of supply chain management problems. While locations for consolidation and coordination are typically known a priori, in adaptive transportation networks this is not the case. The identification of such consolidation locations forms part of the decision making process. Supply chain management problems integrating the designation of consolidation locations with the coordination of long haul and local vehicle routing is not only challenging to solve, but also very difficult to formulate mathematically. In this paper, the first mathematical model integrating location clustering with long haul and local vehicle routing is proposed. This mathematical formulation is used to develop algorithms to find high quality solutions. A novel parallel framework is developed that combines exact and heuristic methods to improve the search for high quality solutions and provide valid bounds. The results demonstrate that using exact methods to guide heuristic search is an effective approach to find high quality solutions for difficult supply chain management problems. Y1 - 2024 U6 - https://doi.org/10.1016/j.cor.2024.106570 SN - 0305-0548 VL - 165 PB - Elsevier BV ER - TY - JOUR A1 - Yokoyama, Ryohei A1 - Takeuchi, Kotaro A1 - Shinano, Yuji A1 - Wakui, Tetsuya T1 - Effect of model reduction by time aggregation in multiobjective optimal design of energy supply systems by a hierarchical MILP method JF - Energy N2 - The mixed-integer linear programming (MILP) method has been applied widely to optimal design of energy supply systems. A hierarchical MILP method has been proposed to solve such optimal design problems efficiently. In addition, a method of reducing model by time aggregation has been proposed to search design candidates accurately and efficiently at the upper level. In this paper, the hierarchical MILP method and model reduction by time aggregation are applied to the multiobjective optimal design. The methods of clustering periods by the order of time series, by the k-medoids method, and based on an operational strategy are applied for the model reduction. As a case study, the multiobjective optimal design of a gas turbine cogeneration system is investigated by adopting the annual total cost and primary energy consumption as the objective functions, and the clustering methods are compared with one another in terms of the computation efficiency. It turns out that the model reduction by any clustering method is effective to enhance the computation efficiency when importance is given to minimizing the first objective function, but that the model reduction only by the k-medoids method is effective very limitedly when importance is given to minimizing the second objective function. Y1 - 2021 U6 - https://doi.org/https://doi.org/10.1016/j.energy.2021.120505 VL - 228 ER - TY - JOUR A1 - Berthold, Timo A1 - Koch, Thorsten A1 - Shinano, Yuji T1 - MILP. Try. Repeat. JF - Proceedings of the 13th International Conference on the Practice and Theory of Automated Timetabling - PATAT 2021 Y1 - 2021 VL - 2 ER - TY - GEN A1 - Hosoda, Junko A1 - Maher, Stephen J. A1 - Shinano, Yuji A1 - Villumsen, Jonas Christoffer T1 - Location, transshipment and routing: An adaptive transportation network integrating long-haul and local vehicle routing N2 - The routing of commodities is a tactical problem in supply chain management that aims to synchronise transportation services connecting a network of warehouses and consolidation locations. This paper considers the routing of commodities in a transportation network that is flexible in response to demand through changes to regional warehouse clustering and the designation of consolidation locations. Traditionally, warehouse clustering and consolidation locations are determined as part of strategic planning that is performed months to years in advance of operations---limiting the flexibility in transportation networks to respond to changes in demand. A mathematical programming-based algorithmic framework is proposed to integrate the strategic decisions of location planning with tactical decisions of vehicle routing and synchronisation. A multi-armed bandit problem is developed to explore warehouse clustering decisions and exploit those that lead to small transportation costs. An extensive computational study will show that the proposed algorithmic framework effectively integrates strategic and tactical planning decisions to reduce the overall transportation costs. T3 - ZIB-Report - 21-12 Y1 - 2021 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-83438 ER - TY - GEN A1 - Tateiwa, Nariaki A1 - Shinano, Yuji A1 - Yamamura, Keiichiro A1 - Yoshida, Akihiro A1 - Kaji, Shizuo A1 - Yasuda, Masaya A1 - Fujisawa, Katsuki T1 - CMAP-LAP: Configurable Massively Parallel Solver for Lattice Problems N2 - Lattice problems are a class of optimization problems that are notably hard. There are no classical or quantum algorithms known to solve these problems efficiently. Their hardness has made lattices a major cryptographic primitive for post-quantum cryptography. Several different approaches have been used for lattice problems with different computational profiles; some suffer from super-exponential time, and others require exponential space. This motivated us to develop a novel lattice problem solver, CMAP-LAP, based on the clever coordination of different algorithms that run massively in parallel. With our flexible framework, heterogeneous modules run asynchronously in parallel on a large-scale distributed system while exchanging information, which drastically boosts the overall performance. We also implement full checkpoint-and-restart functionality, which is vital to high-dimensional lattice problems. Through numerical experiments with up to 103,680 cores, we evaluated the performance and stability of our system and demonstrated its high capability for future massive-scale experiments. T3 - ZIB-Report - 21-16 KW - Discrete optimization KW - Lattice problem KW - Lattice-based cryptography KW - Shortest vector problem KW - Parallel algorithms KW - Ubiquity Generator Framework Y1 - 2021 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-82802 SN - 1438-0064 N1 - Revised version is accepted to HiPC 2021 ER - TY - GEN A1 - Maher, Stephen J. A1 - Ralphs, Ted A1 - Shinano, Yuji T1 - Assessing the Effectiveness of (Parallel) Branch-and-bound Algorithms N2 - Empirical studies are fundamental in assessing the effectiveness of implementations of branch-and-bound algorithms. The complexity of such implementations makes empirical study difficult for a wide variety of reasons. Various attempts have been made to develop and codify a set of standard techniques for the assessment of optimization algorithms and their software implementations; however, most previous work has been focused on classical sequential algorithms. Since parallel computation has become increasingly mainstream, it is necessary to re-examine and modernize these practices. In this paper, we propose a framework for assessment based on the notion that resource consumption is at the heart of what we generally refer to as the “effectiveness” of an implementation. The proposed framework carefully distinguishes between an implementation’s baseline efficiency, the efficacy with which it utilizes a fixed allocation of resources, and its scalability, a measure of how the efficiency changes as resources (typically additional computing cores) are added or removed. Efficiency is typically applied to sequential implementations, whereas scalability is applied to parallel implementations. Efficiency and scalability are both important contributors in determining the overall effectiveness of a given parallel implementation, but the goal of improved efficiency is often at odds with the goal of improved scalability. Within the proposed framework, we review the challenges to effective evaluation and discuss the strengths and weaknesses of existing methods of assessment. T3 - ZIB-Report - 19-03 Y1 - 2019 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-74702 ER - TY - GEN A1 - Shinano, Yuji A1 - Rehfeldt, Daniel A1 - Galley, Tristan T1 - An Easy Way to Build Parallel State-of-the-art Combinatorial Optimization Problem Solvers: A Computational Study on Solving Steiner Tree Problems and Mixed Integer Semidefinite Programs by using ug[SCIP-*,*]-libraries N2 - Branch-and-bound (B&B) is an algorithmic framework for solving NP-hard combinatorial optimization problems. Although several well-designed software frameworks for parallel B&B have been developed over the last two decades, there is very few literature about successfully solving previously intractable combinatorial optimization problem instances to optimality by using such frameworks.The main reason for this limited impact of parallel solvers is that the algorithmic improvements for specific problem types are significantly greater than performance gains obtained by parallelization in general. Therefore, in order to solve hard problem instances for the first time, one needs to accelerate state-of-the-art algorithm implementations. In this paper, we present a computational study for solving Steiner tree problems and mixed integer semidefinite programs in parallel. These state-of-the-art algorithm implementations are based on SCIP and were parallelized via the ug[SCIP-*,*]-libraries---by adding less than 200 lines of glue code. Despite the ease of their parallelization, these solvers have the potential to solve previously intractable instances. In this paper, we demonstrate the convenience of such a parallelization and present results for previously unsolvable instances from the well-known PUC benchmark set, widely regarded as the most difficult Steiner tree test set in the literature. T3 - ZIB-Report - 19-14 Y1 - 2019 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-72804 SN - 1438-0064 ER - TY - CHAP A1 - Shinano, Yuji A1 - Rehfeldt, Daniel A1 - Koch, Thorsten T1 - Building Optimal Steiner Trees on Supercomputers by Using up to 43,000 Cores T2 - Integration of Constraint Programming, Artificial Intelligence, and Operations Research. CPAIOR 2019 N2 - SCIP-JACK is a customized, branch-and-cut based solver for Steiner tree and related problems. ug [SCIP-JACK, MPI] extends SCIP-JACK to a massively parallel solver by using the Ubiquity Generator (UG) framework. ug [SCIP-JACK, MPI] was the only solver that could run on a distributed environment at the (latest) 11th DIMACS Challenge in 2014. Furthermore, it could solve three well-known open instances and updated 14 best-known solutions to instances from the benchmark libary STEINLIB. After the DIMACS Challenge, SCIP-JACK has been considerably improved. However, the improvements were not reflected on ug [SCIP- JACK, MPI]. This paper describes an updated version of ug [SCIP-JACK, MPI], especially branching on constrains and a customized racing ramp-up. Furthermore, the different stages of the solution process on a supercomputer are described in detail. We also show the latest results on open instances from the STEINLIB. Y1 - 2019 U6 - https://doi.org/10.1007/978-3-030-19212-9_35 VL - 11494 SP - 529 EP - 539 PB - Springer ER - TY - CHAP A1 - Shinano, Yuji A1 - Rehfeldt, Daniel A1 - Gally, Tristan T1 - An Easy Way to Build Parallel State-of-the-art Combinatorial Optimization Problem Solvers: A Computational Study on Solving Steiner Tree Problems and Mixed Integer Semidefinite Programs by using ug[SCIP-*,*]-libraries T2 - Proceedings of the 9th IEEE Workshop Parallel / Distributed Combinatorics and Optimization N2 - Branch-and-bound (B&B) is an algorithmic framework for solving NP-hard combinatorial optimization problems. Although several well-designed software frameworks for parallel B&B have been developed over the last two decades, there is very few literature about successfully solving previously intractable combinatorial optimization problem instances to optimality by using such frameworks.The main reason for this limited impact of parallel solvers is that the algorithmic improvements for specific problem types are significantly greater than performance gains obtained by parallelization in general. Therefore, in order to solve hard problem instances for the first time, one needs to accelerate state-of-the-art algorithm implementations. In this paper, we present a computational study for solving Steiner tree problems and mixed integer semidefinite programs in parallel. These state-of-the-art algorithm implementations are based on SCIP and were parallelized via the ug[SCIP-*,*]-libraries---by adding less than 200 lines of glue code. Despite the ease of their parallelization, these solvers have the potential to solve previously intractable instances. In this paper, we demonstrate the convenience of such a parallelization and present results for previously unsolvable instances from the well-known PUC benchmark set, widely regarded as the most difficult Steiner tree test set in the literature. Y1 - 2019 U6 - https://doi.org/10.1109/IPDPSW.2019.00095 SP - 530 EP - 541 PB - IEEE ER - TY - CHAP A1 - Rehfeldt, Daniel A1 - Shinano, Yuji A1 - Koch, Thorsten T1 - SCIP-Jack: An exact high performance solver for Steiner tree problems in graphs and related problems BT - Proceedings of the 7th International Conference on High Performance Scientific Computing T2 - Modeling, Simulation and Optimization of Complex Processes HPSC 2018 N2 - The Steiner tree problem in graphs is one of the classic combinatorial optimization problems. Furthermore, many related problems, such as the rectilinear Steiner tree problem or the maximum-weight connected subgraph problem, have been described in the literature—with a wide range of practical applications. To embrace this wealth of problem classes, the solver SCIP-JACK has been developed as an exact framework for classic Steiner tree and 11 related problems. Moreover, the solver comes with both shared- and distributed memory extensions by means of the UG framework. Besides its versatility, SCIP-JACK is highly competitive for most of the 12 problem classes it can solve, as for instance demonstrated by its top ranking in the recent PACE 2018 Challenge. This article describes the current state of SCIP-JACK and provides up-to-date computational results, including several instances that can now be solved for the first time to optimality. Y1 - 2021 U6 - https://doi.org/10.1007/978-3-030-55240-4_10 PB - Springer ER -