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A column generation mathematical programming approach for a class-faculty assignment problem with preferences

COMPUTATIONAL MANAGEMENT SCIENCE 2015年第2期12卷 297-318页

作者： Al-Yakoob, Salem M. Sherali, Hanif D. Kuwait Univ Coll Sci Dept Math POB 5969 Safat 13060 Kuwait Virginia Tech Grado Dept Ind & Syst Engn 0118 Blacksburg VA 24061 USA

This paper presents a column generation approach for assigning faculty members to sections of offered classes (class-sections) in a case study related to Kuwait University. For a given class, the total number of class-sections to be offered is known;however, the distribution of these class-sections into available time-slots is determined via a mixed-integer programming model that takes into consideration faculty members' aggregate preferences for specific offered classes and the time-slots of the corresponding sections, as well as other restrictions imposed by the Office of the Registrar. Subsequently, upon fixing the time-slot assignments of the class-sections, another mixed-integer programming model is formulated and solved to select weekly schedules for faculty members, while considering their preferences for specific classes and time-slots. In this latter model, each variable corresponds to a feasible schedule of a faculty member, and by exploiting its special structure, we demonstrate that its continuous relaxation can be solved very efficiently via a column generation method in order to heuristically derive a good quality feasible solution. Computational results are provided for a number of test instances, including 10 real cases pertaining to the Department of Mathematics at Kuwait University.

关键词： Class scheduling mixed-integer programming Column generation

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Spectrum allocation problem in elastic optical networks a branch-and-price approach 17

Spectrum allocation problem in elastic optical networks a br...

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17th International Conference on Transparent Optical Networks (ICTON 2015)

作者： Klinkowski, Miroslaw Pioro, Michal Zotkiewicz, Mateusz Walkowiak, Krzysztof Ruiz, Marc Velasco, Luis Natl Inst Telecommun Warsaw Poland Warsaw Univ Technol Warsaw Poland Univ Politecn Cataluna Barcelona Spain

ISBN: (纸本)9781467378802

In the paper we present a branch and price approach to routing and spectrum allocation - a basic optimization problem in elastic optical networks. We formulate the problem as a mixed-integer program for which we develop a branch and price algorithm enhanced with such techniques as cutting planes for improving lower bounds for the optimal objective value, and a greedy and a simulated annealing heuristics for improving the upper bounds. All these elements are combined into an effective optimization procedure. Preliminary results show that the algorithm is able to produce optimal solutions and in a vast majority of the considered cases it performs better than a standard branch-and-bound method implemented in the CPLEX solver.

关键词： Branch and price elastic optical networks mixed-integer programming routing and spectrum allocation

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Elastic Flow Rerouting 7

Elastic Flow Rerouting

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7th International Conference on New Technologies, Mobility and Security (NTMS)

作者： Fouquet, Yoann Nace, Dritan Univ Technol Compiegne Sorbonne Univ CNRS Heudiasyc UMR 7253 CS 60 319 F-60203 Compiegne France

ISBN: (纸本)9781479987849

This work discuss briefly the Elastic Flow Rerouting (EFR)-a traffic restoration strategy for protecting traffic flows in communication networks (including wireless networks). EFR aims at alleviating the trade-off between practicabilty of traffic restoration and the cost of network resources observed in existing networking solutions. We provide a discussion on the strategy and position it among the other strategies.

关键词： survivability traffic restoration mixed-integer programming partial link failures

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Large Neighbourhood Search for Energy-Efficient Train Timetabling

Large Neighbourhood Search for Energy-Efficient Train Timeta...

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27th IEEE International Conference on Tools with Artificial Intelligence (ICTAI)

作者： Grimes, Diarmuid Hurley, Barry Mehta, Deepak O'Sullivan, Barry Natl Univ Ireland Univ Coll Cork Insight Ctr Data Analyt Cork Ireland

ISBN: (纸本)9781509001637

The electric rail sector, like many sectors, is looking for means to reduce its energy consumption and energy cost. In this work we consider the scenario where the utility provider charges based on the maximum consumption over a period. Therefore one wishes to schedule the departure of trains such that the aggregate load is balanced across time periods while satisfying timetabling and resource restrictions. We present an approach which combines the strengths of a number of research areas such as constraint programming, linear programming, mixed-integer programming, and large neighbourhood search. The empirical performance on instances from an ongoing research challenge demonstrates the approach's ability to dramatically reduce the overall energy cost. In addition, we are able to close a number of the instances for which we prove optimality.

关键词： timetabling energy efficiency optimisation large neighbourhood search mixed-integer programming constraint programming

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An assignment-sequencing methodology for scheduling assembly and test operations with multi-pass requirements

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IIE TRANSACTIONS 2015年第2期47卷 153-172页

作者： Gao, Zhufeng Bard, Jonathan F. Chacon, Rodolfo Stuber, John Univ Texas Austin Ind Engn & Operat Res Program Austin TX 78712 USA Texas Instruments Inc Dallas TX 75243 USA

This article presents a three-phase methodology for scheduling assembly and test operations for semiconductor devices. The facility in which these operations are performed is a re-entrant flow shop consisting of several dozen to several hundred machines and up to a 1000 specialized tools. The semiconductor devices are contained in lots, and each lot follows a specific route through the facility, perhaps returning to the same machine multiple times. Each step in the route is referred to as a "pass." In the first phase of the methodology an extended assignment model is solved to simultaneously assign tooling and lots to the machines. Four prioritized objectives are considered: minimize the weighted sum of key device shortages, maximize the weighted sum of lots processed, minimize the number of machines used, and minimize the makespan. In the second phase, lots are optimally sequenced on their assigned machines using the same prioritized objectives. Due to the precedent relations induced by the pass requirements, some lots may have to be delayed or removed from the assignment model solution to ensure that no machine runs beyond the planning horizon. In the third phase, machines are reset to allow additional lots to be processed when tooling is available. The methodology was tested using data provided by the Assembly and Test facility of a leading manufacturer. The results indicate that high-quality solutions can be obtained within 1hour when compared with those obtained with a greedy randomized adaptive search procedure. Cost reductions were observed across all objectives and averaged 62% in the aggregate.

关键词： assembly and test operations Re-entrant flow semiconductor manufacturing mixed-integer programming assignment model

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Sequencing mixed-model assembly lines operating with a heterogeneous workforce

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INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH 2015年第11期53卷 3419-3432页

作者： Cortez, Pamela M. C. Costa, Alysson M. Univ Estadual Feira de Santana Dept Ciencias Exatas Feira De Santana Brazil Univ Melbourne Dept Math & Stat Melbourne Vic Australia

We study the problem of sequencing mixed-model assembly lines operating with a heterogeneous workforce. The practical motivation for this study comes from the context of managing assembly lines in sheltered work centres for the disabled. We propose a general framework in which task execution times are both worker and model dependent. Within this framework, the problem is defined and mathematical mixed-integer models and heuristic procedures are proposed. These include a set of fast constructive heuristics, two local search procedures based on approximate measures using either a solution upper bound or the solution of a linear program and a GRASP metaheuristic. Computational tests with instances adapted from commonly used literature databases are used to validate the proposed approaches. These tests give insight on the quality of the different techniques, which prove to be very efficient both in terms of computational effort and solution quality when compared to other strategies such as a random sampling or the solution of the MIP models using a commercial solver.

关键词： heuristics heterogeneous workers disabled workers mixed-integer programming mixed-model assembly lines

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MIP-and-refine matheuristic for smart grid energy management

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INTERNATIONAL TRANSACTIONS IN OPERATIONAL RESEARCH 2015年第1期22卷 49-59页

作者： Fischetti, Matteo Sartor, Giorgio Zanette, Arrigo Univ Padua DEI I-35131 Padua Italy

In the past years, we have witnessed an increasing interest in smart buildings, in particular for optimal energy management, renewable energy sources, and smart appliances. In this paper, we investigate the problem of scheduling smart appliance operation in a given time horizon with a set of energy sources and accumulators. Appliance operation is modeled in terms of uninterruptible sequential phases with a given power demand, with the goal of minimizing the energy bill fulfilling duration, energy, and user preference constraints. A mixed-integer linear programming (MIP) model and greedy heuristic algorithm are given, which are used in a synergic way. We show how a general purpose (off-the-shelf) MIP-refining procedure can be effectively used for improving, in short computing time, the quality of the solutions provided by the initial greedy heuristic. Computational results confirm the viability of the overall approach, in terms of both solution quality and speed.

关键词： matheuristics mixed-integer programming refinement heuristics energy management smart houses

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Dynamic Reconfiguration of Electrical Power Distribution Systems with Distributed Generation and Storage *

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IFAC-PapersOnLine 2015年第23期48卷 136-141页

作者： Branimir Novoselnik Mato Baotić University of Zagreb Faculty of Electrical Engineering and Computing Unska 3 HR-10000 Zagreb Croatia

In this paper we present a nonlinear model predictive control strategy for dynamic reconfiguration of electrical power distribution systems with distributed generation and storage. Even though power distribution systems are physically built as interconnected meshed networks, as a rule, they operate in a radial topology. The network topology can be modified by changing status of the line switches (opened/closed). The goal of the proposed control strategy is to find the optimal radial network topology and the optimal power references for the controllable generators and energy storage units that will minimize cumulative active power losses while satisfying operating constraints. By utilizing recent results on convex relaxation of the power flow constraints, the proposed dynamic reconfiguration algorithm can be formulated as a mixed-integer second order cone program. Furthermore, if polyhedral approximations of second order cones are used then the underlying optimization problem can be solved as a mixed-integer linear program. Performance of the algorithm is illustrated on a small simulation case study based on actual meteorological and consumption data.

关键词： model predictive control dynamic reconfiguration power distribution system optimal power flow convex relaxation mixed-integer programming conic programming

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Energy Demand Response of Process Systems through Production Scheduling and Control

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IFAC-PapersOnLine 2015年第8期48卷 385-390页

作者： Chudong Tong Nael H. El-Farra Ahmet Palazoglu Department of Chemical Engineering and Materials Science University of California Davis CA 95616 USA

Demand response has become a topic of significant research, development, and deployment over the last few years. The energy demand management is a critical task in industrial process systems for the potential benefits to be realized by promoting the interaction and responsiveness of process operation. However, the dynamic behavior, especially transition trajectories, of the underlying process is seldom taken into account during this task. Furthermore, the incorporation of energy constraints related to electricity pricing and availability is one of the key challenges in this process. The purpose of this study is thus to present a novel optimization formulation for energy demand management in dynamic process systems that takes transition behavior and cost explicitly into account, while simultaneously handling time-sensitive electricity prices. This is accomplished by bringing together production scheduling and transition control through a real-time optimization framework. The dynamic formulation is cast as a mixed-integer nonlinear programming problem and demonstrated using a continuous stirred tank reactor example where the energy required is assumed to be roughly proportional to the material flow.

关键词： Demand Response Energy systems Production Scheduling Control mixed-integer programming Chemical Processes

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Optimal Agricultural Credit Association Branch Office Locations

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Journal of Agricultural and Applied Economics 2015年第1期35卷 127-141页

作者： Timi M. Scaletta Jeffrey R. Stokes Frostburg State University Frostburg MD and Department of Agricultural Economics and Rural Sociology The Pennsylvania State University University Park PA Department of Agricultural Economics and Rural Sociology The Pennsylvania State University University Park PA

Since the farm financial crisis of the 1980s, Farm Credit System banks continue to merge and consolidate to enhance competitiveness. Two mixed-integer programming models of AgChoice Agricultural Credit Association (ACA), a recently merged ACA in Pennsylvania, were developed to determine the optimal number, location, and territory of branches. The approach suggests useful information can be determined regarding the reconfiguration process after bank mergers, especially given the fact that the current AgChoice ACA configuration is available for comparison purposes.

关键词： Agricultural Credit Association compromise programming Farm Credit System location model mixed-integer programming C61 G21 Q14

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