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A two-phase approach to solve the synchronized bin-forklift scheduling problem

JOURNAL OF INTELLIGENT MANUFACTURING 2018年第3期29卷 651-657页

作者： El Hachemi, Nizar Saddoune, Mohammed El Hallaoui, Issmail Rousseau, Louis-Martin Univ Mohammed V Agdal Ecole Mohammadia Ingn Dept Genie Ind Rabat Morocco Univ Hassan 2 Fac Sci Tech Mohammedia Casablanca Morocco Ecole Polytech Montreal Dept Math & Genie Ind Montreal PQ Canada Univ Montreal CIRRELT CP 6128Succ Ctr Ville Montreal PQ H3C 3J7 Canada GERAD CP 6128Succ Ctr Ville Montreal PQ H3C 3A7 Canada

In this paper, we propose a two-phase approach to solve a combined routing and scheduling problem that occurs in the textile industry: fabrics are dyed by dye-jets and transported by forklifts. The objective is to minimize the cost of the unproductive activities, i.e., the dye-jet setup times and the forklift waiting time. The first phase solves an integer linear program to assign jobs (fabrics) to dye-jets while minimizing the setup cost;we compare an arc-based and a path-based formulation. The second phase uses a mixed-integer linear program for the dye-jet scheduling and both the routing and scheduling of forklifts. Experiments are performed on real data provided by a major multinational company, and larger test problems are randomly generated to assess the algorithm. The tests were conducted using Cplex 12.6.0 and a column generation solver. The numerical results show that our approach is efficient in terms of both solution quality and computational time.

关键词： Scheduling Column generation mixed-integer programming Textile industry

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A General Framework for Process Scheduling

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AICHE JOURNAL 2011年第3期57卷 695-710页

作者： Sundaramoorthy, Arul Maravelias, Christos T. Univ Wisconsin Dept Chem & Biol Engn Madison WI 53706 USA

Existing methods for process scheduling can be broadly classified as network-based or sequential. The former are used to address problems where different batches of the same or different tasks are freely mixed or split, whereas the latter are used to address problems where batch mixing/splitting is not allowed. A framework is proposed that allows us to: (1) express scheduling problems in facilities that consist of network and sequential, as well as continuous subsystems, (2) formulate mixed-integer programming (MIP) scheduling models for such problems, and (3) solve the resulting MIP formulations effectively. The proposed framework bridges the gap between network and sequential approaches, thereby addressing the major formulation challenge in the area of process scheduling, namely, the development of a framework that can be used to address a wide spectrum of problems. (C) 2010 American Institute of Chemical Engineers AIChE J, 57: 695-710, 2011

关键词： process scheduling mixed-integer programming

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Analyzing the robustness of an array of wireless access points to mobile jammers

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COMPUTERS & INDUSTRIAL ENGINEERING 2017年 107卷 25-38页

作者： Schweitzer, David Jafari-Marandi, Ruholla Medal, Hugh Mississippi State Univ Dept Ind & Syst Engn POB 9542 Mississippi State MS 39762 USA

We present an approach for measuring the vulnerability of a wireless network. Our metric, n-Robustness, measures the change in a network's total signal strength resulting from the optimal placement of n jammers by an attacker. Toward this end, we develop a multi-period mixed-integer programming interdiction model that determines the movement of n jammers over a time horizon so as to minimize the total signal strength of users during a sustained jamming attack. We compared several solution approaches for solving our model including a Lagrangian relaxation heuristic, a genetic algorithm, and a stage decomposition heuristic. We tested our approach on a wireless trace dataset developed as part of the Wireless Topology Discovery project at the University of California San Diego. We found that the Lagrangian approach, which performed best overall, finds a close-to-optimal solution while requiring much less time than solving the MIP directly. We then illustrate the behavior of our model on a small example taken from the dataset as well as a set of experiments. Through our experiments we conclude that the total signal power follows a sigmoid curve as we increase the number of jammers and access points. We also found that increasing access points only improves network robustness initially;after that the benefit levels off. In addition, we found that the problem instances we considered have an n-Robustness of between 39 and 69%, indicating that the value of the model parameters (e.g., number of jammers, number of time periods) has an effect on robustness. (C) 2017 Elsevier Ltd. All rights reserved.

关键词： Networks mixed-integer programming Security Interdiction Location analysis

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AN INTEGRATED DP-MIP MODEL FOR OPTIMAL CROP MIX SELECTION WITH DEFICIT IRRIGATION

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ASIA-PACIFIC JOURNAL OF OPERATIONAL RESEARCH 2008年第5期25卷 625-647页

作者： Azaiez, M. N. King Saud Univ Dept Ind Engn Riyadh 11421 Saudi Arabia

We consider a region suffering from irrigation water scarcity. Candidate crops differ widely in their growth cycles, economic values and water consumption. We develop an integrated dynamic programming-mixed integer programming model to solve for optimal land exploitation over a one year horizon for multiple crops. The model applies deficit irrigation in order to increase the irrigated area at the expense of reducing crop yield per unit area. The dynamic program (DP) guarantees that deficit irrigation is only considered when it is economically efficient. Moreover, it provides optimal combinations of irrigation levels for each growth stage of candidate crops, accounting for the varying impact of water stress over time and the seasonal supply of irrigation water. The output of the DP serves as input to the mixed integer program (MIP). The MIP selects the most pro. table crops in the right sequence to benefit the most from the crop-yield dependence on crop predecessor and allocates water and land optimally to maximize total profit. The objective function accounts for the attitude of the decision-maker toward risk by incorporating in its expression a risk-aversion coefficient.

关键词： Water management deficit irrigation mixed-integer programming dynamic programming crop scheduling

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The zone-based dynamic facility layout problem

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INFOR 2019年第1期57卷 1-31页

作者： Kulturel-Konak, Sadan Penn State Berks Management Informat Syst Reading PA 19610 USA

The dynamic facility layout problem (DFLP) is to decide the locations of the departments in a facility over multiple planning periods. The main challenge in the DFLP is that there are two conflicting objectives of the problem: minimizing the material handling cost and the rearrangement cost. The cost of changing the structure of the layout over the planning horizon is also considered. Therefore, we model and solve the unequal area zone-based DFLP (ZDFLP) where the dimensions of the departments are decision variables and the departments are assigned to flexible zones with a pre-structured positioning. A zone-based block layout inherently includes possible aisle structures which can easily be adapted to the material handling system in use. This is particularly important in the DFLP because the changes in a block layout may require structural modifications in the material handling system, which in turn may be very costly. The proposed approach also considers determining relative department locations, their dimensions, as well as input/output (I/O) points concurrently for the first time in the literature. A new matheuristic, which combines concepts from simulated annealing, variable neighbourhood search, and mixed-integer programming, is used to solve the ZDFLP with promising results.

关键词： Facilities planning and design zone-based dynamic facility layout problem mixed-integer programming simulated annealing variable neighbourhood search

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Risk-Averse Shortest Path Interdiction

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INFORMS JOURNAL ON COMPUTING 2016年第3期28卷 527-539页

作者： Song, Yongjia Shen, Siqian Virginia Commonwealth Univ Dept Stat Sci & Operat Res Med Coll Virginia Campus Richmond VA 23284 USA Univ Michigan Dept Ind & Operat Engn Ann Arbor MI 48109 USA

We consider a Stackelberg game in a network where a leader minimizes the cost of interdicting arcs and a follower seeks the shortest distance between given origin and destination nodes under uncertain arc traveling cost. In particular, we consider a risk-averse leader, who aims to keep high probability that the follower's traveling distance is longer than a given threshold, interpreted by a chance constraint. Under the assumption of a wait-and-see follower-i.e., the follower selects a shortest path after seeing realizations of the random arc cost-we propose a branch-and-cut algorithm and apply lifting techniques to exploit the combinatorial structure of the risk-averse leader's interdiction problem. We demonstrate the computational efficacy of our approaches, risk-averse interdiction solution patterns, and result sensitivity, by testing instances of randomly generated grid networks and real-world transportation networks.

关键词： stochastic network interdiction chance constraint mixed-integer programming branch and cut lifting

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Real-Time Control of an Electric Vehicle Charging Station While Tracking an Aggregated Power Setpoint

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IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS 2020年第5期56卷 5750-5761页

作者： Rudnik, Roman Wang, Cong Reyes-Chamorro, Lorenzo Achara, Jagdish Boudec, Jean-Yves Le Paolone, Mario Ecole Polytech Fed Lausanne CH-1015 Lausanne Switzerland Univ Austral Chile Fac Ciencias Ingn Valdivia 5090000 Chile

We consider the problem of controlling the charging of electric vehicles (EVs) connected to a single charging station that follows an aggregated power setpoint from a main controller of the local distribution grid. To cope with volatile resources such as load or distributed generation, this controller manages in real time the flexibility of the energy resources in the distribution grid and uses the charging station to adapt its power consumption. The aggregated power setpoint might exhibit rapid variations due to other volatile resources of the local distribution grid. However, large power jumps and minicycles could increase the EV battery wear. Hence, our first challenge is to properly allocate the powers to EVs so that such fluctuations are not directly absorbed by EV batteries. We assume that EVs are used as flexible loads and that they do not supply the grid. As the EVs have a minimum charging power that cannot be arbitrarily small, and as the rapid fluctuations of the aggregated power setpoint could lead to frequent disconnections and reconnections, the second challenge is to avoid these disconnections and reconnections. The third challenge is to fairly allocate the power in the absence of the information about future EVs arrivals and departures, as this information might be unavailable in practice. To address these challenges, we formulate an online optimization problem and repeatedly solve it by using a mixed-integer-quadratic program. To do so in real time, we develop a heuristic that reduces the number of integer variables. We validate our method by simulations with real-world data.

关键词： Batteries Charging stations Real-time systems Optimization Switches Resource management Delays Battery protection dispatching of active distribution networks electric vehicles (EVs) fairness mixed-integer programming real-time control

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Cardinality-constrained portfolio selection based on collaborative neurodynamic optimization

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NEURAL NETWORKS 2022年 145卷 68-79页

作者： Leung, Man-Fai Wang, Jun Hong Kong Metropolitan Univ Sch Sci & Technol Kowloon Hong Kong Peoples R China City Univ Hong Kong Dept Comp Sci Kowloon Hong Kong Peoples R China City Univ Hong Kong Sch Data Sci Kowloon Hong Kong Peoples R China

Portfolio optimization is one of the most important investment strategies in financial markets. It is practically desirable for investors, especially high-frequency traders, to consider cardinality constraints in portfolio selection, to avoid odd lots and excessive costs such as transaction fees. In this paper, a collaborative neurodynamic optimization approach is presented for cardinality-constrained portfolio selection. The expected return and investment risk in the Markowitz framework are scalarized as a weighted Chebyshev function and the cardinality constraints are equivalently represented using introduced binary variables as an upper bound. Then cardinality-constrained portfolio selection is formulated as a mixed-integer optimization problem and solved by means of collaborative neurodynamic optimization with multiple recurrent neural networks repeatedly repositioned using a particle swarm optimization rule. The distribution of resulting Pareto-optimal solutions is also iteratively perfected by optimizing the weights in the scalarized objective functions based on particle swarm optimization. Experimental results with stock data from four major world markets are discussed to substantiate the superior performance of the collaborative neurodynamic approach to several exact and metaheuristic methods. (C) 2021 Elsevier Ltd. All rights reserved.

关键词： Cardinality constraint Neurodynamic optimization mixed-integer programming Portfolio selection

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Minimizing average project team size given multi-skilled workers with heterogeneous skill levels

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COMPUTERS & OPERATIONS RESEARCH 2016年第Jun.期70卷 163-179页

作者： Walter, Matthias Zimmermann, Juergen Tech Univ Clausthal Inst Management & Econ Operat Res Grp Julius Albert Str 2 D-38678 Clausthal Zellerfeld Germany

Many firms face the challenging task of staffing concurrent projects such that the skill requirements of each project can be satisfied by the respective team of workers. We consider a staffing problem where each worker can be assigned to several projects at a time. A high total number of assignments implies large project teams and scattering of workers across projects. Large teams come along with productivity losses due to increased coordination effort and social loafing while scattering incurs losses due to frequent switching between projects. To curb these inefficiencies, we formulate a mixed-integer linear program that minimizes average project team size and, thus, scattering. The program accounts for multi skilled workers with heterogeneous skill levels who must also fulfill duties within their departments. We prove that the problem is NP-hard in the strong sense and outline valid inequalities that accelerate the solution by a commercial branch-and-cut solver. For large-scale instances, we devise three construction heuristics, each of which is embedded in a multi-pass procedure. Our performance analysis reveals that a heuristic based on the drop principle offers the best compromise between solution quality and computation time. Limitations of the proposed approach, managerial insights, and areas of application are discussed. (C) 2015 Elsevier Ltd. All rights reserved.

关键词： Multi-project staffing Multi-skilled workers Team size Social loafing mixed-integer programming Multi-pass heuristics

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Fixed-Charge Transportation with Product Blending

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TRANSPORTATION SCIENCE 2012年第2期46卷 281-295页

作者： Papageorgiou, Dimitri J. Toriello, Alejandro Nemhauser, George L. Savelsbergh, Martin W. P. . Georgia Inst Technol H Milton Stewart Sch Ind & Syst Engn Atlanta GA 30332 USA Univ So Calif Daniel J Epstein Dept Ind & Syst Engn Los Angeles CA 90089 USA Univ Newcastle Sch Math & Phys Sci Callaghan NSW 2308 Australia

Numerous planning models within the chemical, petroleum, and process industries involve coordinating the movement of raw materials in distribution networks so they can be blended into final products. The uncapacitated fixed-charge transportation problem with blending (FCTPwB) studied in this paper captures a core structure encountered in many of these environments. We model the FCTPwB as a mixed-integer linear program, and we derive two classes of facets, both exponential in size, for the convex hull of solutions for the problem with a single consumer and show that they can be separated in polynomial time. Furthermore, we prove that, in certain situations, these classes of facets along with the continuous relaxation of the original constraints yield a description of the convex hull. Finally, we present a computational study that demonstrates that these classes of facets are effective in reducing the integrality gap and solution time for more general instances of the FCTPwB with arc capacities and multiple consumers.

关键词： blending fixed-charge transportation mixed-integer programming polyhedral study

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