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A Hierarchical Hybrid Heuristic-Optimization Approach for Multi-Product Assembly Line Design Problem

Procedia Manufacturing 2019年 39卷 1067-1075页

作者： Gürsel A Süer Roohollah Younes Sinaki Azadeh Sadeghi Department of Industrial and System Engineering Ohio University Athens 45701 OH United States

In this research, an alternative parallel assembly line design strategy for multi products is proposed. Assigning operators to the parallel assembly stations optimally is an essential task specifically when the production volume is considerably high and the numbers of required operators are more than the number of assembly operations. The primary objective in the parallel assembly line problem is to balance more than one assembly line together. To deal with this problem a three phase hierarchy methodology is developed: (1) based on the assembly network for each product, operations are grouped into stations for various configuration. (2) In order to determine how many operators should be assigned to each station, a mathematical model is used and parallel stations are designed. (3) The number of assembly lines is determined with the objective of minimizing total number of operators required in the system. This approach guarantees that minimum number of workers is obtained thus maximizing overall system efficiency. This study is the extension of Suer’s (1998) study in which only one product was considered.

关键词： Assembly line balancing mixed-integer programming Parallel stations Parallel Assembly line Multi products Heuristic

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Robust auction design under multiple priors by linear and integer programming

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ANNALS OF OPERATIONS RESEARCH 2018年第1-2期260卷 233-253页

作者： Kocyigit, Cagil Bayrak, Halil I. Pinar, Mustafa C. Bilkent Univ Dept Ind Engn TR-06800 Ankara Turkey Ecole Polytech Fed Lausanne Lausanne Switzerland

It is commonly assumed in the optimal auction design literature that valuations of buyers are independently drawn from a unique distribution. In this paper we study auctions under ambiguity, that is, in an environment where valuation distribution is uncertain itself, and present a linear programming approach to robust auction design problem with a discrete type space. We develop an algorithm that gives the optimal solution to the problem under certain assumptions when the seller is ambiguity averse with a finite prior set and the buyers are ambiguity neutral with a prior . We also consider the case where all parties, the buyers and the seller, are ambiguity averse, and formulate this problem as a mixed integer programming problem. Then, we propose a hybrid algorithm that enables to compute an optimal solution for the problem in reduced time.

关键词： Optimal auction design Robustness Multiple priors Ambiguity Linear programming mixed-integer programming

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Outer-approximation algorithms for nonsmooth convex MINLP problems

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OPTIMIZATION 2018年第6期67卷 797-819页

作者： Delfino, A. de Oliveira, W. UTFPR Univ Tecnol Fed Parana DAMAT Math Dept Pato Branco Brazil PSL Res Univ CMA MINES ParisTech Sophia Antipolis France

In this work, we combine outer-approximation (OA) and bundle method algorithms for dealingwithmixed-integer non-linear programming (MINLP) problems with nonsmooth convex objective and constraint functions. As the convergence analysis of OA methods relies strongly on the differentiability of the involved functions, OA algorithms may fail to solve general nonsmooth convex MINLP problems. In order to obtain OA algorithms that are convergent regardless the structure of the convex functions, we solve the underlying OA's non-linear subproblems by a specialized bundle method that provides necessary information to cut off previously visited (non-optimal) integer points. This property is crucial for proving (finite) convergence of OA algorithms. We illustrate the numerical performance of the given proposal on a class of hybrid robust and chanceconstrained problems that involve a random variable with finite support.

关键词： mixed-integer programming nonsmooth optimization chance-constrained programming

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A Stochastic-Goal mixed-integer programming approach for integrated stock and bond portfolio optimization

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COMPUTERS & INDUSTRIAL ENGINEERING 2011年第4期61卷 1285-1295页

作者： Stoyan, Stephen J. Kwon, Roy H. Univ So Calif Daniel J Epstein Dept Ind & Syst Engn Los Angeles CA 90089 USA Univ Toronto Dept Mech & Ind Engn Toronto ON Canada

We consider a Stochastic-Goal mixed-integer programming (SGMIP) approach for an integrated stock and bond portfolio problem. The portfolio model integrates uncertainty in asset prices as well as several important real-world trading constraints. The resulting formulation is a structured large-scale problem that is solved using a model specific algorithm that consists of a decomposition, warm-start, and iterative procedure to minimize constraint violations. We present computational results and portfolio return values in comparison to a market performance measure. For many of the test cases the algorithm produces optimal solutions, where CPU time is improved greatly. (C) 2011 Elsevier Ltd. All rights reserved.

关键词： Stochastic programming Goal programming mixed-integer programming Geographical decomposition

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Adaptive reallocation of cybersecurity analysts to sensors for balancing risk between sensors

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SERVICE ORIENTED COMPUTING AND APPLICATIONS 2018年第2期12卷 123-135页

作者： Shah, Ankit Ganesan, Rajesh Jajodia, Sushil Cam, Hasan George Mason Univ Ctr Secure Informat Syst Mail Stop 5B5 Fairfax VA 22030 USA Army Res Lab 2800 Powder Mill Rd Adelphi MD 20783 USA

Cyber Security Operations Center (CSOC) is a service-oriented system. Analysts work in shifts, and the goal at the end of each shift is to ensure that all alerts from each sensor (client) are analyzed. The goal is often not met because the CSOC is faced with adverse conditions such as variations in alert generation rates or in the time taken to thoroughly analyze new alerts. Current practice at many CSOCs is to pre-assign analysts to sensors based on their expertise, and the alerts from the sensors are triaged, queued, and presented to analysts. Under adverse conditions, some sensors have more number of unanalyzed alerts (backlogs) than others, which results in a major security gap for the clients if left unattended. Hence, there is a need to dynamically reallocate analysts to sensors;however, there does not exist a mechanism to ensure the following objectives: (i) balancing the number of unanalyzed alerts among sensors while maximizing the number of alerts investigated by optimally reallocating analysts to sensors in a shift, (ii) ensuring desirable properties of the CSOC: minimizing the disruption to the analyst to sensor allocation made at the beginning of the shift when analysts report to work, balancing of workload among analysts, and maximizing analyst utilization. The paper presents a technical solution to achieve the objectives and answers two important research questions: (i) detection of triggers, which determines when-to reallocate, and (ii) how to optimally reallocate analysts to sensors, which enable a CSOC manager to effectively use reallocation as a decision-making tool.

关键词： Cybersecurity analysts Adaptive reallocation Balance risk between sensors Reactive scheduling Goal programming mixed-integer programming

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Energy-oriented production planning with time-dependent energy prices

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Procedia CIRP 2019年 80卷 245-250页

作者： Christoph Johannes Matthias G. Wichmann Thomas S. Spengler Institute of Automotive Management and Industrial Production Technische Universität Braunschweig Mühlenpfordtstr. 23 38106 Braunschweig Germany

Based on a more sustainable power generation, companies are faced so far with increasing energy costs for industrial production processes. However, in the future there is a possibility to reduce energy costs by the occurrence of time-dependent energy prices in the course of a day. In order to use these time-dependent energy prices best possible and to manufacture the products at minimal decision relevant costs, production planning approaches have to consider energy costs. To date, time-dependent energy prices are considered in numerous Job Shop Scheduling Problems, but in only few simultaneous lot-sizing and scheduling approaches. Hence, an appropriate model formulation for the consideration of time-dependent energy prices in simultaneous lot-sizing and scheduling and an investigation of the cost saving potential are missing. For this purpose, the Energy-Oriented Lot-sizing and Scheduling Problem (EOLSP) is introduced in this contribution. Furthermore, the energy and total cost saving potential of the presented model formulation compared to conventional planning is discussed within an illustrative example for a pre-crushing system in a recycling company.

关键词： Energy-oriented production planning lot-sizing scheduling time-dependent energy prices mixed-integer programming

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Learning customized and optimized lists of rules with mathematical programming

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MATHEMATICAL programming COMPUTATION 2018年第4期10卷 659-702页

作者： Rudin, Cynthia Ertekin, Seyda Duke Univ Dept Comp Sci Durham NC 27706 USA Duke Univ Dept Elect & Comp Engn Durham NC 27706 USA Duke Univ Dept Stat Sci Durham NC 27706 USA Middle Eastern Tech Univ Dept Comp Engn Ankara Turkey MIT Sloan Sch Management Cambridge MA 02139 USA

We introduce a mathematical programming approach to building rule lists, which are a type of interpretable, nonlinear, and logical machine learning classifier involving IF-THEN rules. Unlike traditional decision tree algorithms like CART and C5.0, this method does not use greedy splitting and pruning. Instead, it aims to fully optimize a combination of accuracy and sparsity, obeying user-defined constraints. This method is useful for producing non-black-box predictive models, and has the benefit of a clear user-defined tradeoff between training accuracy and sparsity. The flexible framework of mathematical programming allows users to create customized models with a provable guarantee of optimality. The software reviewed as part of this submission was given the DOI (Digital Object Identifier) https://***/10.5281/zenodo.1344142.

关键词： mixed-integer programming Decision trees Decision lists Sparsity Interpretable modeling Associative classification 68T05-Computer Science Artificial intelligence Learning and adaptive systems

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The impact of filtering in a branch-and-cut algorithm for multicommodity capacitated fixed charge network design

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EURO JOURNAL ON COMPUTATIONAL OPTIMIZATION 2018年第2期6卷 143-184页

作者： Chouman, Mervat Crainic, Teodor Gabriel Gendron, Bernard Effat Univ Coll Business Jeddah Saudi Arabia Univ Quebec Montreal Dept Management & Technol Sch Management Interuniv Res Ctr Enterprise Networks Logist & Tr Montreal PQ Canada Univ Montreal Interuniv Res Ctr Enterprise Networks Logist & Tr Dept Informat & Rech Operat Montreal PQ Canada

In this paper, we present a state-of-the-art branch-and-cut (B&C) algorithm for the multicommodity capacitated fixed charge network design problem (MCND). This algorithm combines bounding and branching procedures inspired by the latest developments in mixed-integer programming (MIP) software tools. Several filtering methods that exploit the structure of the MCND are also developed and embedded within the B&C algorithm. These filtering methods apply inference techniques to forbid combinations of values for some variables. This can take the form of adding cuts, reducing the domains of the variables, or fixing the values of the variables. Our experiments on a large set of randomly generated instances show that an appropriate selection of filtering techniques allows the B&C algorithm to perform better than the variant of the algorithm without filtering. These experiments also show that the B&C algorithm, with or without filtering, is competitive with a state-of-the-art MIP solver.

关键词： mixed-integer programming Multicommodity capacitated fixed charge network design Branch-and-cut Filtering

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A Mathematical Modelling and Optimization Approach for a Maritime Facility Location Transshipment Problem

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Informatica 2019年第4期29卷 609-632页

作者： Al-Yakoob, Salem M. Sherali, Hanif D. Department of Mathematics College of Science Kuwait University P.O. Box: 5969 Safat 13060 State of Kuwait Grado Department of Industrial and Systems Engineering (0118) Virginia Tech Blacksburg VA 24061 USA. E-mails:

This paper presents an optimization based mathematical modelling approach for a single source single destination crude oil facility location transshipment problem. We began by formulating a mixed-integer nonlinear programming model and use a rolling horizon heuristic to find an optimal location fora storage facility within a restricted continuous region. We next design a hybrid two-stage algorithm that combines judicious facility locations resulting from the proposed model into a previously developed column generation approach. The results indicate that improved overall operational costs can be achieved by strategically determining cost-effective locations of the transshipment facility.

关键词： mixed-integer programming vessel scheduling transportation inventory

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A mixed-integer programming approach to strategic planning of chemical centres: A case study in the UK

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COMPUTERS & CHEMICAL ENGINEERING 2011年第8期35卷 1359-1373页

作者： Liu, Pei Whitaker, Alan Pistikopoulos, Efstratios N. Li, Zheng Univ London Imperial Coll Sci Technol & Med CPSE Dept Chem Engn London SW7 2AZ England Tsinghua Univ State Key Lab Power Syst Dept Thermal Engn Beijing 100084 Peoples R China

Chemical centres provide great potential to tackle the worldwide energy and environmental issues via integrated chemical synthesis and heat and power generation. However, planning of chemical centres still involves many formidable challenges, including locating production sites, arrangement of transportation, and selection of appropriate technologies. These problems become further complicated when considering the geographic situation of a region under study. In this paper, we propose a multi-period mixed-integer programming (MIP) approach to the optimal planning of chemical centres. The planning horizon is firstly divided into several time intervals, and the planning region is represented by a grid. Then a superstructure representation is developed to capture all available logistic and technical options. Based on the superstructure representation, an MIP problem is developed, and by solving it an optimal planning strategy can be obtained. A real-life case study for the UK follows, where the UK is divided into a grid of 34 cells. (C) 2011 Elsevier Ltd. All rights reserved.

关键词： Strategic planning Process integration Chemical synthesis Emissions reduction Superstructure mixed-integer programming

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