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Logic-based Benders decomposition for gantry crane scheduling with transferring position constraints in a rail-road container terminal

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ENGINEERING OPTIMIZATION 2021年第1期53卷 86-106页

作者： Guo, Peng He, Xun Luan, Yulin Wang, Yi Southwest Jiaotong Univ Sch Mech Engn Chengdu Peoples R China Technol & Equipment Rail Transit Operat & Mainten Chengdu Peoples R China Auburn Univ Dept Math & Comp Sci Montgomery AL USA

Rail-road container terminals can be seen as buffers within a large logistics network encompassing hinterland distribution systems. They are used as temporary storage points for containers such that unloading operations from a train and loading operations onto a truck need not be synchronized. Container transferring operation implemented by gantry cranes is one of the most important issues to ensure efficient logistics. To enable efficient container transfer, this article considers the special features of container movement, and integrates the starting position and the ending position of container movement into the gantry crane scheduling problem. In order to solve the proposed problem, this article develops two models: first using mixed integer programming, and secondly using constraint programming (CP). Since the problem is computationally intractable for realistic sizes, this article also proposes a logic-based Benders decomposition (LBBD) methodology to solve it. This method exploits a natural decomposition of the studied problem into a relaxed master problem (RMP) solved by mixed integer programming (MIP), and a series of sub-problems, solved separately by MIP and CP. Computational experiments are performed on generated instances, the structures of which are designed to follow the practical application. The computational results show that the CP approach is better suited to solve the proposed problem with small-sized and medium-sized instances compared with MIP and LBBD. In addition, the LBBD framework is far superior to mixed integer programming on all but a few small instances, and it is highly effective in finding good-quality solutions for larger cases with up to 100 tasks within a reasonable runtime. Moreover, the results find that LBBD using constraint programming to solve the sub-problems usually outperforms LBBD with mixed integer programming on the instances tested.

关键词： Rail-road container terminal crane scheduling Benders decomposition constraint programming mixed integer programming

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INTERFACE MODELING FOR QUALITY AND RESOURCE MANAGEMENT

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LOGICAL METHODS IN COMPUTER SCIENCE 2021年第2期17卷 19:1-19:34页

作者： Hendriks, Martijn Geilen, Marc Goossens, Kees de Jong, Rob Basten, Twan Eindhoven Univ Technol Eindhoven Netherlands ESI TNO Eindhoven Netherlands Philips Med Syst Int BV Best Netherlands

We develop an interface-modeling framework for quality and resource management that captures configurable working points of hardware and software components in terms of functionality, resource usage and provision, and quality indicators such as performance and energy consumption. We base these aspects on partially-ordered sets to capture quality levels, budget sizes, and functional compatibility. This makes the framework widely applicable and domain independent (although we aim for embedded and cyber-physical systems). The framework paves the way for dynamic (re-)configuration and multi-objective optimization of component-based systems for quality- and resource-management purposes.

关键词： constraint programming multi-objective combinatorial optimization Pareto algebra embedded and cyber-physical systems quality of service

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A note on computational approaches for the antibandwidth problem

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CENTRAL EUROPEAN JOURNAL OF OPERATIONS RESEARCH 2021年第3期29卷 1057-1077页

作者： Sinnl, Markus Univ Vienna Fac Business Dept Stat & Operat Res Econ & Stat Vienna Austria Johannes Kepler Univ Linz Inst Prod & Logist Management Linz Austria

In this note, we consider the antibandwidth problem, also known as dual bandwidth problem, separation problem and maximum differential coloring problem. Given a labeled graph (i.e., a numbering of the vertices of a graph), the antibandwidth of a node is defined as the minimum absolute difference of its labeling to the labeling of all its adjacent vertices. The goal in the antibandwidth problem is to find a labeling maximizing the antibandwidth. The problem is NP-hard in general graphs and has applications in diverse areas like scheduling, radio frequency assignment, obnoxious facility location and map-coloring. There has been much work on deriving theoretical bounds for the problem and also in the design of metaheuristics in recent years. However, the optimality gaps between the best known solution values and reported upper bounds for the HarwellBoeing Matrix-instances, which are the commonly used benchmark instances for this problem, are often very large (e.g., up to 577%). Moreover, only for three of these 24 instances, the optimal solution is known, leading the authors of a state-of-the-art heuristic to conclude "HarwellBoeing instances are actually a challenge for modern heuristic methods". The upper bounds reported in literature are based on the theoretical bounds involving simple graph characteristics, i.e., size, order and degree, and a mixed-integer programming (MIP) model. We present new MIP models for the problem, together with valid inequalities, and design a branch-and-cut algorithm and an iterative solution algorithm based on them. These algorithms also include two starting heuristics and a primal heuristic. We also present a constraint programming approach, and calculate upper bounds based on the stability number and chromatic number. Our computational study shows that the developed approaches allow to find the proven optimal solution for eight instances from literature, where the optimal solution was unknown and also provide reduced gaps for eleven ad

关键词： Graph labeling Integer programming constraint programming Clique problem Bandwidth

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COPRICSI: constraint-PRogrammed Initial Circuit SIzing

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INTEGRATION-THE VLSI JOURNAL 2021年 76卷 148-158页

作者： Abel, Inga Neuner, Maximilian Graeb, Helmut Tech Univ Munich Arcisstr 21 D-80333 Munich Germany

This paper presents a new method to automate the sizing of analog circuits. The method emulates the manual design procedure. The sizing task is formulated as a constraint programming problem. Two new algorithms are introduced: First, a hierarchical structural analysis of functional blocks that automatically sets up the analytical equations for the sizing. And second, a heuristic to guide the branching process of a constraint programming solver. We achieve a reproduction of the manual proceeding of designers and at the same time an automation of the set-up of the design problem, reducing the set-up effort to seconds. The method is primarily designed for operational amplifiers. More than 20 circuits, including different variants of two-stage, folded-cascode, telescopic and symmetrical op-amps, are considered at this time. This paper presents a runtime comparison of the newly developed branching heuristic with a generic branching heuristic on 20 different circuits. Furthermore, sizing results for a two-stage op-amp with transistors in weak inversion and a folded-cascode op-amp with common-mode feedback circuit are presented to show the effectiveness of the approach.

关键词： Analog circuit design CMOS Operational amplifiers constraint programming

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Transfer-robot task scheduling in job shop

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INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH 2021年第3期59卷 813-823页

作者： Ham, Andy Liberty Univ Ind & Syst Engn Lynchburg VA 24515 USA

This paper studies a simultaneous scheduling of production and material transfer in a job shop environment. The simultaneous scheduling approach has been recently adopted by warehouse operations, wherein transbots pick up jobs and deliver to pick-machines for processing that requires a simultaneous scheduling of jobs, transbots, and machines. However, both a large proportion of literature and real-world scheduling systems consider only one side of the problem. In our study, machines and transbot are both considered as constraining resources. The contributions of this paper are twofold. First, we propose a novel application of constraint programming for the job shop scheduling problem (JSP) with transbots, significantly outperforming all other benchmark approaches in the literature and proving optimality of the well-known benchmark instances, for the first time. Second, we propose a medium-scale benchmark instance.

关键词： Robot task scheduling job shop simultaneous scheduling constraint programming

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Vehicle and reliable driver scheduling for public bus transportation systems

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TRANSPORTATION RESEARCH PART B-METHODOLOGICAL 2021年 145卷 290-301页

作者： Andrade-Michel, Alejandro Rios-Solis, Yasmin A. Boyer, Vincent Univ Autonoma Nuevo Leon Syst Engn San Nicolas De Los Garza Nuevo Leon Mexico Tecnol Monterrey Escuela Ingenier & Ciencias Monterrey Mexico

We propose the bus vehicle and reliable driver scheduling problem that is an integrated approach for the vehicle and the crew scheduling problems considering driver's reliability information to reduce the number of no-covered trips along the day and thus improve the user's satisfaction. An exact constraint programming model is proposed and compared with a variable neighborhood search that incorporates the driver's reliability and the trip's importance. The obtained trip-vehicle-driver assignments are evaluated on many scenarios with a Monte Carlo method to simulate the driver's absenteeism. Experimental results on randomly generated instances based on a real case study show our methodologies' efficiency and the enormous gains in covered trips when the drivers' reliability is considered. (C) 2021 Elsevier Ltd. All rights reserved.

关键词： Vehicle scheduling Driver scheduling Driver's reliability constraint programming Variable neighborhood search Monte carlo method

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A Declarative Approach to New Product Development Project Prototyping

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IEEE INTELLIGENT SYSTEMS 2021年第5期36卷 88-94页

作者： Relich, Marcin Bocewicz, Grzegorz Rostek, Katarzyna Banaszak, Zbigniew A. Univ Zielona Gora Dept Comp Applicat Econ PL-65417 Zielona Gora Poland Koszalin Univ Technol PL-75453 Koszalin Poland Koszalin Univ Technol Fac Elect & Comp Sci PL-75453 Koszalin Poland Warsaw Univ Technol PL-00661 Warsaw Poland

Today, project-oriented companies often have difficulties completing projects according to schedule. Currently used decision-support solutions allow decision makers to estimate the cost of a new product development project, and compare the estimated cost to the target cost. The proposed approach provides a framework for searching for possible project completion scenarios, which allow us to reach the target cost. The focus of this article is a project prototyping problem described in terms of a constraint satisfaction problem. The proposed method uses artificial neural networks, to identify relationships between variables, and constraint programming, to search for project completion scenarios within the company's resources and project requirements. The results of an experiment indicate that constraint programming provides effective search strategies for finding admissible solutions. Consequently, the proposed approach allows decision makers to obtain alternative project completion scenarios within the limits imposed by project requirements.

关键词： Search problems Project management Planning constraint handling Software Product development Intelligent systems computational intelligence constraint programming constraint satisfaction problem decision support systems project management

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Mathematical programming approach to productivity improvement in wind turbine-blade manufacturing through a case study

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ENGINEERING WITH COMPUTERS 2021年第4期37卷 3843-3856页

作者： Baykasoglu, Adil Dudakli, Nurhan Senol, Mumin Emre Komurcu, Feyzi Dokuz Eylul Univ Fac Engn Dept Ind Engn Izmir Turkey

Wind energy has attracted remarkable attention in recent years as one of the most important renewable energy sources. However, wind energy production is still a costly process and one of the reasons is production processes which are usually not optimized. The purpose of this paper is to improve the efficiency of spar cap production process as an important phase of a wind turbine blade production in a manufacturing system. For this purpose, the present paper introduces a new optimization problem for optimal assignment of fiberglass rolls along the spar cap. In order to solve the roll allocation problem (RAP) optimally, two alternative mathematical programming models based on mixed-integer programming (MIP) and constraint programming (CP) are developed. Subsequently, two cases form a real manufacturing setting are presented and solved by using both MIP and CP models. Although proposed models are capable to solve problems optimally, it is observed that CP outperforms MIP. Solving RAP optimally reduces walking time/distance of workers considerably and provides significant improvements in comparison with current manufacturing practices. Besides, the total operation time will also decrease correlatively, and this will lead to an increase in productivity of turbine blade production in the studied system.

关键词： Wind turbine blade manufacturing Roll allocation problem Mixed-integer programming constraint programming Productivity improvement

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constraint-based Diversification of JOP Gadgets

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JOURNAL OF ARTIFICIAL INTELLIGENCE RESEARCH 2021年 72卷 1471-1505页

作者： Tsoupidi, Rodothea Myrsini Lozano, Roberto Castaneda Baudry, Benoit KTH Royal Inst Technol Stockholm Sweden Univ Edinburgh Edinburgh Midlothian Scotland

Modern software deployment process produces software that is uniform, and hence vulnerable to large-scale code-reuse attacks, such as Jump-Oriented programming (JOP) attacks. Compiler-based diversification improves the resilience and security of software systems by automatically generating different assembly code versions of a given program. Existing techniques are efficient but do not have a precise control over the quality, such as the code size or speed, of the generated code variants. This paper introduces Diversity by Construction (DivCon), a constraint-based compiler approach to software diversification. Unlike previous approaches, DivCon allows users to control and adjust the conflicting goals of diversity and code quality. A key enabler is the use of Large Neighborhood Search (LNS) to generate highly diverse assembly code efficiently. For larger problems, we propose a combination of LNS with a structural decomposition of the problem. To further improve the diversification efficiency of DivCon against JOP attacks, we propose an application-specific distance measure tailored to the characteristics of JOP attacks. We evaluate DivCon with 20 functions from a popular benchmark suite for embedded systems. These experiments show that DivCon's combination of LNS and our application-specific distance measure generates binary programs that are highly resilient against JOP attacks (they share between 0.15% to 8% of JOP gadgets) with an optimality gap of <= 10%. Our results confirm that there is a trade-off between the quality of each assembly code version and the diversity of the entire pool of versions. In particular, the experiments show that DivCon is able to generate binary programs that share a very small number of gadgets, while delivering near-optimal code. For constraint programming researchers and practitioners, this paper demonstrates that LNS is a valuable technique for finding diverse solutions. For security researchers and software engineers, DivCon extend

关键词： constraint programming

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A constraint programming approach to designing a newspaper distribution system

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INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS 2013年第1期145卷 132-138页

作者： Russell, Robert Univ Tulsa Collins Coll Business Tulsa OK 74104 USA

This paper presents a constraint programming approach using a modeling language and CP optimizer to aid in the coordination of the production and delivery of multi-product newspapers to bulk delivery locations. The distribution problem is modeled as an open vehicle routing problem with time windows and zoning constraints. The use of a high level modeling language eliminates the need to develop custom low-level computer codes to solve the problem. The methodology is applied to the newspaper production and distribution problem in a major metropolitan area. Computational results are presented and show significant improvement relative to a previous metaheuristic approach using tabu search. (C) 2013 Elsevier B.V. All rights reserved.

关键词： Newspaper logistics constraint programming Open vehicle routing problem with time windows Metaheuristic Tabu search

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