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Joint planning of service engineers and spare parts

EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2018年第1期271卷 97-108页

作者： Sleptchenko, Andrei Al Hanbali, Ahmad Zijm, Henk Khalifa Univ Sci & Technol Coll Engn Dept Ind & Syst Engn POB 127788 Abu Dhabi U Arab Emirates King Fahd Univ Petr & Minerals Coll Comp Sci & Engn Syst Engn Dept Dhahran 31261 Saudi Arabia Univ Twente Fac Behav Management & Social Sci Dept Ind Engn & Business Informat Syst POB 217 NL-7500 AE Enschede Netherlands

We analyze the joint optimization of spare parts inventories and workforce allocation in a single-site maintenance system. In this system, for each failure, a service engineer with a necessary replacement part has to be allocated. If one of the required resources is not available, the incoming failure request is routed to an external provider, such as a centralized repair facility or a sub-contractor. We study multiple failure types (related to failing components) with exponentially distributed inter-failure times. The system repair times and the replenishment times of the spare parts inventory are also exponentially distributed. The inventory replenishment is done according to a Base-Stock policy. The objective is to minimize the total system cost consisting of annual holding costs of the spare parts and the service engineers, and incidental outsourcing costs. For the joint optimization of the resources, we propose a mixed-integer programming (MIP) formulation using the balance equations of the Markov Chain representation of the system. Furthermore, we provide a simple and efficient heuristic that produces close-to-optimal (<0.3% difference) results, for solving larger instances. Using the proposed optimization methods and real-life data, we analyze the optimal balance between the costs of the resources and the outsourcing costs and show how the outsourcing rates and the total costs behave for different system parameters. (C) 2018 Elsevier B.V. All rights reserved.

关键词： Maintenance Spare Parts Service engineers Markov process mixed-integer programming

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Least cost influence propagation in (social) networks

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MATHEMATICAL programming 2018年第1期170卷 293-325页

作者： Fischetti, Matteo Kahr, Michael Leitner, Markus Monaci, Michele Ruthmair, Mario Univ Padua DEI Padua Italy Univ Vienna Dept Stat & Operat Res Vienna Austria Univ Bologna DEI Bologna Italy

Influence maximization problems aim to identify key players in (social) networks and are typically motivated from viral marketing. In this work, we introduce and study the Generalized Least Cost Influence Problem (GLCIP) that generalizes many previously considered problem variants and allows to overcome some of their limitations. A formulation that is based on the concept of activation functions is proposed together with strengthening inequalities. Exact and heuristic solution methods are developed and compared for the new problem. Our computational results also show that our approaches outperform the state-of-the-art on relevant, special cases of the GLCIP.

关键词： Influence maximization mixed-integer programming Social network analysis

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A superstructure optimization approach for process synthesis under complex reaction networks

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CHEMICAL ENGINEERING RESEARCH & DESIGN 2018年 137卷 589-608页

作者： Ramapriya, Gautham Madenoor Won, Wangyun Maravelias, Christos T. Univ Wisconsin Dept Chem & Biol Engn Madison WI 53706 USA Univ Wisconsin DOE Great Lakes Bioenergy Res Ctr Madison WI 53726 USA

In this work, we present mixed integer linear programming methods for the synthesis of processes that involve complex reaction networks. Specifically, we consider the modeling of reactors and interconnecting streams in systems where the composition of the reactor inlet streams can vary substantially, thereby making the determination of the limiting component as well as the calculation of the stream heating/cooling and power requirements challenging. First, towards the modeling of reactors, we develop an extent-based method which detects the limiting reactant of each reaction occurring in parallel with others, based on the inlet flows of the reactants. Second, we develop a computationally tractable method for the calculation of the work and heating/cooling duty needed to condition any stream of a process based on simple calculations that can be performed offline. Finally, we present how the two aforementioned components can be integrated in an optimization model generated based on a process superstructure. We demonstrate the application of the developed methods for the synthesis of a biorefinery. (C) 2018 Institution of Chemical Engineers. Published by Elsevier B.V. All rights reserved.

关键词： Process systems engineering Reactor network synthesis mixed-integer programming Biofuels

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Packaged gas supply chain planning with network-wide SKU rationalization

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INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS 2018年 204卷 346-357页

作者： Malinowski, Ethan Karwan, Mark H. Sun, Lei Pinto, Jose M. Univ Buffalo Dept Ind & Syst Engn Buffalo NY 14260 USA Praxair Inc 175 E Pk Dr Tonawanda NY 14150 USA Praxair Inc 10 Riverview Dr Danbury CT 06810 USA

Effective SKU rationalization is advantageous when applied to businesses with a high variety of product offerings. Advantages may include lower production costs, inventory simplifications, and system-wide reductions in transportation costs. We apply SKU rationalization in the form of a variant of product substitution, towards an industrial packaged gas supply chain problem which includes production, allocation, and distribution decisions. An effective mixed-integer programming formulation is developed, capable of handling additional line investment, varying degrees of substitution, economies-of-scale in production, as well as network-wide planning decisions in the supply chain. A case study based on historical data is used for testing, followed by computational results and policy implications in the form of customer incentivization.

关键词： SKU rationalization Product substitution Packaged gas supply chain mixed-integer programming Incentivization

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Exploring K-best solutions to enrich network design decision-making

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OMEGA-INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE 2018年 78卷 139-164页

作者： Guazzelli, Caue Sauter Cunha, Claudio B. Univ Sao Paulo Escola Politecn Dept Transportat Engn Caixa Postal 61548 BR-05424970 Sao Paulo SP Brazil Ctr Univ Inst Maua Tecnol Escola Engn Maua Praca Maua 1 BR-09580050 Sao Caetano do Sul SP Brazil

In this paper, we explore alternative solutions to the Capacitated Fixed Charge Facility Location problem (CFCFL) that usually arises in Supply Chain Network Design problems. More specifically, we aim to investigate in which cases these solutions can be considered as good as the optimal one from the point of view of decision-making in real-world problems. A method, as well as four enhancement variations, based on a mixed-integer programming (MIP) model is proposed, which allows K-best alternative solutions to be obtained. The method and its variations were applied to two benchmark instance sets available in the literature and the computational times were evaluated. The results have shown that the gap between the optimal solutions and the 20-best alternative ones were, on average, less than 1%;more surprisingly, 63.8% of all these alternative solutions had a gap smaller than 0.5%. This suggests that our approach may be used to identify whether near-optimal alternative solutions can yield to a better overall solution from the point of view of the decision-maker, by allowing other qualitative attributes to be considered. We were also able to rate the robustness of some selected facilities since many candidates have appeared in all 20 best solutions. In addition, the results may also suggest a way to measure the difficulty of benchmark instances for combinatorial problems and thus enhance the comparison of different heuristics proposed to solve them;not to mention that the uncertainty in input data of such strategic problems may reduce the relevance of the effort to find the best solution in the contexts in which several high-quality solutions arise. (C) 2017 Elsevier Ltd. All rights reserved.

关键词： Location Supply chain network design K-best solutions mixed-integer programming Alternative solutions approach

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Optimization-free robust MPC around the terminal region

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AUTOMATICA 2018年 95卷 229-235页

作者： Darup, Moritz Schulze Moennigmann, Martin Univ Paderborn Automat Control Grp D-33098 Paderborn Germany Ruhr Univ Bochum Automat Control & Syst Theory D-44801 Bochum Germany

We present a novel dual-mode MPC scheme that significantly reduces the computational effort of robust MPC (RMPC). Specifically, we propose a method for the computation of a large set C on which no optimal control problem (OCP) needs to be solved online. The method is motivated by the trivial observation that, for classical MPC, no optimization is required for the states in the terminal set T, because the unconstrained linear-quadratic regulator is optimal there. While this observation cannot be directly transferred to RMPC, we show that suitable sets C exist in the neighborhood of T and state an algorithm for their computation. We stress that the resulting sets C are significantly larger than robust positively invariant sets that are typically exploited in RMPC and on which it is well-known that no OCP needs to be solved online. The approach is illustrated with three examples for which we observe a reduction of the numerical effort between 22.36% and 95.60%. (C) 2018 Elsevier Ltd. All rights reserved.

关键词： Optimal control Predictive control Robust control Terminal control mixed-integer programming

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Optimal design of switched Ethernet networks implementing the Multiple Spanning Tree Protocol

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DISCRETE APPLIED MATHEMATICS 2018年 234卷 114-130页

作者： Fortz, Bernard Gouveia, Luis Joyce-Moniz, Martim Univ Libre Bruxelles Dept Informat CP 212Blvd Triomphe B-1050 Brussels Belgium INRIA Lille Nord Europe INOCS Villeneuve Dascq France Univ Lisbon Fac Ciencias Dept Estat & Invest Operac Bloco C-2 Campo Grande P-1700 Lisbon Portugal

Switched Ethernet networks rely on the Spanning Tree Protocol (STP) to ensure a cycle free connectivity between nodes, by reducing the topology of the network to a spanning tree. The Multiple Spanning Tree Protocol (MSTP) allows for the providers to partition the traffic in the network and assign it to different virtual local area networks, each satisfying the STP. In this manner, it is possible to make a more efficient use of the physical resources in the network. In this paper, we consider the traffic engineering problem of finding optimal designs of switched Ethernet networks implementing the MSTP, such that the worst-case link utilization is minimized. We show that this problem is N P-hard. We propose three mixed-integer linear programming formulations for this problem. Through a large set of computational experiments, we compare the performance of these formulations. Until now, the problem was almost exclusively solved with heuristics. Our objective here is providing a first comparison of different models that can be used in exact methods. (C) 2016 Elsevier B.V. All rights reserved.

关键词： Telecommunications Traffic engineering Multiple Spanning Tree Protocol Network design mixed-integer programming

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Robust scheduling to minimize the weighted number of late jobs with interval due-date uncertainty

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COMPUTERS & OPERATIONS RESEARCH 2018年 91卷 13-20页

作者： Drwal, Maciej Wroclaw Univ Sci & Technol Dept Comp Sci Wroclaw Poland

We consider the class of single machine scheduling problems with the objective to minimize the weighted number of late jobs, under the assumption that completion due-dates are not known precisely at the time when decision-maker must provide a schedule. It is assumed that only the intervals to which the due-dates belong are known. The concept of maximum regret is used to define robust solution. A polynomial time algorithm is given for the case when weights of jobs are all equal. A mixed-integer linear programming formulation is provided for the general case, and computational experiments are reported. (C) 2017 Elsevier Ltd. All rights reserved.

关键词： Scheduling Robust optimization Uncertainty mixed-integer programming

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An integrated framework for inventory management and transportation of refined petroleum products: Pipeline or marine?

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APPLIED MATHEMATICAL MODELLING 2018年 55卷 224-247页

作者： Siddiqui, Atiq Verma, Manish Verter, Vedat Imam Abdulrahman Bin Faisal Univ Coll Business Adm Dammam Saudi Arabia McMaster Univ DeGroote Sch Business Hamilton ON Canada McGill Univ Desautels Fac Management Montreal PQ Canada

We study the integrated problem of managing inventory of refined petroleum products, and their multi-modal (ships and pipeline) transportation between a refinery and the served distribution centers. It is important that the transportation decisions are driven not just by the inventory levels and customer demand, but also the environmental risks associated with different refined products. A bi-objective mixed integer linear programming optimization model (MILP) is proposed, where constituent components were independently developed and then interfaced to capture the complexity of the resulting integrated model. A time-based decomposition heuristic is also employed to solve the integrated problem. The proposed framework was used to study a number of problem instances generated using a realistic infrastructure in the United States, and the resulting analyses lead to the following inferences: pipeline is the preferred mode of transportation only when cost is the sole consideration;on the other hand, when environmental risks are considered marine is the preferred mode for most of the refined petroleum products, except for heavier oils;and, the proportion of traffic on the two modes is a function of the type and volume of products, and the number of vessels available at the start of the planning horizon. (C) 2017 Elsevier Inc. All rights reserved.

关键词： Inventory management Transport-mode choice Hazardous materials mixed-integer programming Time-based heuristic

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Relaxing leaf-motion restrictions in dynamic multileaf collimator leaf sequencing

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MEDICAL PHYSICS 2018年第11期45卷 5263-5276页

作者： Mirzapour, Seyed Ali Salari, Ehsan Wichita State Univ Dept Ind Syst & Mfg Engn Wichita KS 67260 USA

Purpose Methods Traditionally, unidirectional leaf-sweeping schemes have been employed to deliver IMRT plans using the dynamic multileaf collimator (DMLC) technique. The goal of this research is to investigate the potential impact of relaxing the leaf-motion restrictions in DMLC IMRT on the beam-modulation quality and the delivery efficiency. This research relaxes the initial and final leaf-position constraints as well as the unidirectional leaf-motion restriction that have been traditionally imposed on DMLC leaf sequencing and develops exact and heuristic solution approaches to allow for an unconstrained and bidirectional leaf motion. The exact approach employs mixed-integer programming (MIP) techniques and the proposed heuristic method uses stochastic search algorithms while utilizing the special structure of the problem. The trade-off between beam-modulation quality and delivery efficiency is quantified and compared to that of unidirectional leaf-sweeping schemes. Results Conclusions The performance of the developed approaches is tested on liver and head-and-neck cancer cases. Results validate that unconstrained leaf trajectories can significantly improve the beam-modulation quality at small beam-on time values. However, this gain reduces as the available beam-on time increases. Additionally, the proposed heuristic approach can achieve near-optimal solutions with significantly smaller computational effort compared to the MIP solution approach. Unconstrained leaf trajectories have the potential to enhance the fluence-modulation quality for cases in which the available beam-on time is limited. This gain is primarily attributed to the relaxation of the initial and final leaf positions. The unidirectionality restriction alone does not appear to be a limiting factor.

关键词： DMLC IMRT mixed-integer programming unidirectional leaf sweeping

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