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A hybrid multi-stage stochastic programming-robust optimization model for maximizing the supply chain of a forest-based biomass power plant considering uncertainties

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JOURNAL OF CLEANER PRODUCTION 2016年第Part4期112卷 3285-3293页

作者： Shabani, Nazanin Sowlati, Taraneh Univ British Columbia Dept Wood Sci Ind Engn Res Grp Vancouver BC V6T 1Z4 Canada

Electricity generated from forest-based biomass is an attractive source of renewable energy. However, the cost of generating heat and/or electricity from it is relatively high due to the low energy density of wood, high moisture content and variations in its quality and availability. models have been developed to optimize the supply chain and reduce the cost per kilowatt hour generated. This paper focuses on incorporating uncertainty in the supply chain of such a model. The model considers the tactical supply chain planning of a power plant over a one-year time horizon with monthly time steps. Uncertain parameters which impact the net profit of the power plant include 'biomass quality,' namely moisture content and higher heating value, and 'monthly available biomass' from different suppliers. Robust optimization is used to model uncertainty in the quality of biomass. Then a hybrid, multi-stage, 'stochastic programming-robust optimization' model is presented in order to simultaneously include uncertainty in biomass quality and biomass availability. It is demonstrated that the hybrid model takes advantage of both modelling approaches to balance the profit estimates and the tractability to various circumstances. The model provides solution considering all instances of the uncertain parameters within the defined sets and scenario tree. The results revealed a major trade-off between profit and range of biomass quality. Profit decreased by up to 23% when there was +/- 13% variation in moisture content and +/- 5% change in higher heating value. The model achieved a biomass purchase cost that was lower than the current commercial costs at the power plant. Implementing the model could prevent production curtailment and undesirable fluctuation in storage levels which occurred in the past due to variations in biomass availability and quality. (C) 2015 Elsevier Ltd. All rights reserved.

关键词： Forest-based biomass Uncertainty mixed integer programming model Supply chain optimization Multi-stage stochastic model Robust optimization

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modeling a Generalized Resource Constrained Multi Project Scheduling Problem Integrated with a Forward-Backward Supply Chain Planning

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IFAC-PapersOnLine 2016年第12期49卷 1283-1288页

作者： Gholizadeh-Tayyar, S. Dupont, L. Lamothe, J. Falcon, M. Toulouse University Ecole des Mines d'Albi-Carmaux Industrial Engineering Department Albi France TBC Générateur d'Innovation Colomiers France

Generalized Resource Constrained Multi Project Scheduling Problem, GRCMPSP, is issue of determining a scheduling plan for executing projects’ activities under satisfaction of precedence relationship between activities and availability of resources. This paper focuses on the resources’ availability. To deal with feeding nonrenewable recourses over periods they are demanded and to define a production-transportation plan for them, our proposed mixed integer programming model integrates GRCMPSP with Supply Chain Planning model. Also, to establish a plan for assigning required amounts of renewable resources, it supposes possibility of renting supplementary quantities. This assumption leads the model to define an optimum assignment under considering rent cost of additional resources and penalty cost may originate from lateness of the activities. The results are shown from applying the model on a project called CRIB A, which is defined to reduce energy consumption level of buildings in France. © 2016

关键词： integer programming Energy utilization Scheduling Supply chains mixed integer programming mixed integer programming model Precedence relationships Production transportation Reduce energy consumption Renewable resource Resource constrained multi project scheduling problems Supply chain planning

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Two-machine job shop problem for makespan minimization under availability constraint

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IFAC-PapersOnLine 2016年第28期49卷 132-137页

作者： Benttaleb, Mourad Hnaien, Faicel Yalaoui, Farouk ICD-LOSI Université de Technologie de Troyes UMR CNRS 6281 12 Rue Marie Curie Troyes CedexCS 42060-10004 France

We treat a two-machine job shop scheduling problem with availability constraint on one machine to minimize the makespan. We consider the deterministic case where the unavailability period, corresponding to preventive maintenance tasks, is known in advance and fixed. We assume that jobs are non-preemptive. First, two mixed-integer programming (MIP) models are first presented. Some propositions concerning the optimality of Jackson's algorithm when availability constraint exists is provided. Then a branch and bound (B&B) method is developed to solve the problem. The obtained results prove the efficiency of the proposed B&B. © 2016

关键词： Job shop scheduling Availability Branch and bound method integer programming Machine shops Preventive maintenance Problem solving Scheduling Availability constraints bound Branch Job shop scheduling problems Makespan minimization mixed integer programming mixed integer programming model Unavailability periods

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A Piecewise Linear model for Stochastic Disassembly Line Balancing

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IFAC-PapersOnLine 2016年第12期49卷 932-937页

作者： Altekin, F. Tevhide School of Management Sabanci University Orhanli Tuzla Istanbul34956 Turkey

Disassembly lines are used so as to recover both economic and ecological value residing in collected end-of-life products while meeting environmental legislation. Due to the nature of the disassembly operations, disassembly tasks exhibit higher levels of uncertainty. So as to incorporate the variability in task times while designing disassembly lines, this paper deals with the stochastic disassembly line balancing problem with the objective of minimizing the number of stations. Task times are assumed to be normally distributed random variables with known means and standard deviations. A chance-constrained piecewise-linear mixed integer programming model is proposed. The computational experiments using the cell phone problem demonstrate that the proposed model can yield on average 2% improvements compared to a stochastic station oriented ranked positional heuristic. © 2016

关键词： Stochastic models integer programming Mobile phones Normal distribution Piecewise linear techniques Stochastic systems Disassembly Disassembly line balancing Distributed random variables Environmental legislations Line balancing mixed integer programming model Piecewise linear modeling Stochastic task

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A biased random-key genetic algorithm for wireless backhaul network design

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APPLIED SOFT COMPUTING 2015年 33卷 150-169页

作者： Andrade, Carlos E. Resende, Mauricio G. C. Zhang, Weiyi Sinha, Rakesh K. Reichmann, Kenneth C. Doverspike, Robert D. Miyazawa, Flavio K. Univ Estadual Campinas Inst Comp BR-13083852 Campinas SP Brazil AT&T Labs Res Network Evolut Res Dept Middletown NJ 07748 USA Amazon Com Inc Math Optimizat & Planning Grp Seattle WA 98109 USA

This paper describes a biased random-key genetic algorithm for a real-world wireless backhaul network design problem. This is a novel problem, closely related to variants of the Steiner tree problem and the facility location problem. Given a parameter h, we want to build a forest where each tree has at most h hops from the demand nodes, where traffic originates, to the root nodes where each tree is rooted. Candidate Steiner nodes do not have any demand but represent locations where we can install cellsites to cover the traffic and equipment to backhaul the traffic to the cellular core network. Each Steiner node can cover demand nodes within a given distance, subject to a capacity constraint. The aggregate set of constraints may make it impossible to cover or backhaul all demands. A revenue function computes the revenue associated with the total amount of traffic covered and backhauled to the root nodes. The objective of the problem is to build a forest that maximizes the difference between the total revenue and the cost associated with the installed equipment. Although we will have a forest when we consider only the backhaul links and root nodes, the addition of demand vertices can induce undirected cycles, resulting in a directed acyclic graph. We consider instances of this problem with several additional constraints that are motivated by the requirements of real-world telecommunication networks. (C) 2015 Elsevier B.V. All rights reserved.

关键词： Wireless backhaul network design Small cells Genetic algorithm mixed integer programming model

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Algorithms for Scheduling Problem with Different Deterioration Jobs under Depending on Waiting Times 6

Algorithms for Scheduling Problem with Different Deteriorati...

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6th IEEE International Conference on Software Engineering and Service Science (ICSESS)

作者： Wu, Huaping Huang, Min Chongqing Univ Technol Chongqing 400054 Peoples R China Northeastern Univ Coll Informat Sci & Engn Shenyang 110819 Liaoning Peoples R China Northeastern Univ State Key Lab Synthet Automat Proc Ind Shenyang 110819 Liaoning Peoples R China

ISBN: (纸本)9781479983537

In this paper, a single machine scheduling problem with deterioration jobs is investigated. It focuses on considering a new deterioration model and different deterioration rates for minimizing the makespan. Firstly, a mixed integer programming model for the scheduling problem is presented. Secondly, according to characteristics of the problem, dominance properties and lower bounds are proposed and integrated into the Branch and Bound algorithm (B&B). Thirdly, for solving a large-scale problem, the heuristic algorithm is proposed. The numerical experiments show that when the size of the problem is small, the B&B algorithm can obtain the optimal solutions in a reasonable time. ILOG CPLEX can also obtain the optimal solutions of the problem when the size of the problem is medium. A heuristic algorithm can obtain good near-optimal solutions in no more than 1s. The results of numerical experiments show that model, B&B and the heuristic algorithm are effective.

关键词： Single machine Deterioration model mixed integer programming model CPLEX Heuristic algorithm

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An inventory routing problem with soft time windows

An inventory routing problem with soft time windows

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12th International Symposium on Operations Research and its Applications in Engineering, Technology and Management (ISORA 2015)

作者： Zhenping Li Chongyu Jiang Lulu Jiang School of Information Beijing Wuzi University Beijing China

ISBN: (纸本)9781510821224

Inventory routing problem (IRP) which is a problem integrated with inventory control and vehicle routing is a typical NP-hard problem, and also is the key of inventory and distribution coordinated optimization in the vendor managed inventory (VMI). An IRP of petrol secondary delivery system on the background of petroleum and petrochemical enterprise is investigated. Given a set of homogeneous vehicles with capacity constraint, which can be used for fuel distribution from one depot to a set of petrol stations that have deterministic fuel consumption, to minimize the total cost of the system, a mixed integer linear programming model of the inventory routing problem with soft time window (IRPSTW) is established. The model is solved by Lingo software. Simulations are done on an example. Based on solutions with different weight coefficients, we analyse the impact on the total cost by vehicle assignment cost and travel cost. The results of this paper provide a theoretical basis to solve the petrol secondary distribution problem of multiple terminal stations.

关键词： inventory routing problem mixed integer programming model petrol secondary distribution soft time window

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Algorithms for Scheduling Problem with Differen Deterioration Jobs under Depending on Waiting Times

Algorithms for Scheduling Problem with Differen Deterioratio...

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2015 6th IEEE International Conference on Software Engineering and Service Science(ICSESS 2015)

作者： Huaping Wu Min Huang Chongqing University of Technology College of Information Science and Engineering Northeastern University State Key Laboratory of Synthetical Automation for Process Industries Northeastern University

In this paper, a single machine scheduling problem with deterioration jobs is investigated. It focuses on considering a new deterioration model and different deterioration rates for minimizing the makespan. Firstly, a mixed integer programming model for the scheduling problem is presented. Secondly, according to characteristics of the problem, dominance properties and lower bounds are proposed and integrated into the Branch and Bound algorithm（B＆B）. Thirdly, for solving a large-scale problem, the heuristic algorithm is proposed. The numerical experiments show that when the size of the problem is small, the B＆B algorithm can obtain the optimal solutions in a reasonable time. ILOG CPLEX can also obtain the optimal solutions of the problem when the size of the problem is medium. A heuristic algorithm can obtain good near-optimal solutions in no more than 1s. The results of numerical experiments show that model, B＆B and the heuristic algorithm are effective.

关键词： Single machine Deterioration model mixed integer programming model CPLEX Heuristic algorithm

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A cut-and-solve-based algorithm for optimal lane reservation with dynamic link travel times

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INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH 2014年第4期52卷 1003-1015页

作者： Fang, Yunfei Chu, Feng Mammar, Said Che, Ada Fuzhou Univ Sch Management Fuzhou 350002 Peoples R China Univ Evry Val Essonne Lab IBISC EA 4526 Evry France Univ Technol Troyes Lab LOSI Troyes France Hefei Univ Technol Sch Transportat Engn Hefei Peoples R China Northwestern Polytech Univ Sch Management Xian 710072 Peoples R China

This paper investigates an optimal lane reservation problem with dynamic link travel times via a lane reservation strategy. This strategy is to select some existing general-purpose lanes from a transportation network and convert them to reserved lanes for some special road users only so that a time-guaranteed transportation can be ensured. However, such conversion may cause traffic impact such as an increase of link travel times on adjacent lanes due to the disallowing utilisation of reserved lanes by general-purpose vehicles. Thus, the considered problem aims to design reserved lane-based paths for the time-guaranteed transportation with the objective of minimising the total traffic impact caused by the conversion. Different from lane reservation problems with constant link travel times in the literature, the considered problem assumes dynamic link travel times, which is proved NP-hard. The problem is initially formulated as a mixed integer non-linear programming model. In order to solve it, the non-linear model is reformulated as an equivalent linear model and a cut-and-solve-based algorithm is proposed to obtain optimal solutions. Experimental tests on randomly generated instances show that the overall performance of the proposed algorithm outperforms a direct use of a commercial CPLEX MIP solver.

关键词： optimal lane reservation dynamic link travel times mixed integer programming model cut-and-solve method

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An epsilon-free approach for finding the most efficient unit in DEA

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APPLIED MATHEMATICAL modelLING 2014年第13期38卷 3182-3192页

作者： Toloo, Mehdi Tech Univ Ostrava Fac Econ Dept Business Adm Ostrava Czech Republic

Data envelopment analysis (DEA), considering the best condition for each decision making unit (DMU), assesses the relative efficiency and partitions DMUs into two sets: efficient and inefficient. Practically, in traditional DEA models more than one efficient DMU are recognized and these models cannot rank efficient DMUs. Some studies have been carried out aiming at ranking efficient DMUs, although in some cases only discrimination of the most efficient unit is desirable. Furthermore, several investigations have been done for finding the most CCR-efficient DMU. The basic idea of the majority of them is to introduce an integrated model which achieves an optimal common set of weights (CSW). These weights help us identify the most efficient unit in an identical condition. Recently, Toloo (2012) [13] proposed a new mixed integer programming (MIP) model to find the most BCC-efficient unit. Based on this study, we propose a new basic integrated linear programming (LP) model to identify candidate DMUs for being the most efficient unit;next a new MIP integrated DEA model is introduced for determining the most efficient DMU. Moreover, these models exclude the non-Archimedean epsilon and consequently the optimal solution of these models can be obtained, straightforwardly. We claim that the most efficient unit, which could be obtained from all other integrated models, has to be one of the achieved candidates from the basic integrated LP model. Two numerical examples are illustrated to show the variant use of these models in different important cases. (C) 2013 Elsevier Inc. All rights reserved.

关键词： Data envelopment analysis mixed integer programming model Epsilon-free approach The most efficient unit Common set of weights Facility layout design

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