EditorialDiscrete Optimization for Dynamic Systems of OperationsManagement in Data-Driven Society

Lu Zhen ,1 ShuaianWang,2 Xiaobo Qu,3 and XinchangWang4

1 School of Management, Shanghai University, Shanghai, China2The Hong Kong Polytechnic University, Hung Hom, Hong Kong3Chalmers University of Technology, Gothenburg, Sweden4Mississippi State University, Starkville, USA

Correspondence should be addressed to Lu Zhen; lzhen@shu.edu.cn

Received 7 May 2019; Accepted 7 May 2019; Published 15 May 2019

Copyright © 2019 Lu Zhen et al.�is is an open access article distributed under the Creative Commons Attribution License, whichpermits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Society is being reshaped by large volumes of data generatedfrom various operations, and research in handling dynamicissues related to data-driven systems has greatly increased inthe past decades, where most rely upon discrete optimizationmodels for handling dynamic features contained in opera-tions management (OM) activities. With the rapid growth incomputational technologies, including datamining technolo-gies, discrete event simulation techniques, and intelligencealgorithms, OM relies more and more on optimal solutions(or their approximates) based on high-performance modelsand algorithms.

�is special issue collects 32 original research contribu-tions that present recent advances in models and algorithmsconcerning discrete optimizations on dynamic OM systemsrelevant to the data-driven society. In particular, the papersaddress the topics related to discrete optimization method-ologies for stochastic OM problems, dynamic programmingbased exact methods for stochastic OM problems, systemdynamics in behavior OM for E-commerce, data-driven riskanalysis andmodeling forOMdecisions in dynamic contexts,data-driven models for dynamic supply chain management,etc. It is hoped that this special issue will help the integrationof the latest research achievements in the relevant field.

�e paper by S. Li et al. entitled “Probability Mech-anism Based Particle Swarm Optimization Algorithm andIts Application in Resource-Constrained Project SchedulingProblems” proposes a new probability mechanism basedparticle swarm optimization (PMPSO) algorithm to solve

combinatorial optimization problems by introducing newparticles based on the optimal particles in the populationand the historical optimal particles in the individual changes.�is method is applied to solve resource-constrained projectscheduling problems and the experimental results are quiteencouraging.

S. Zhang et al. in the paper entitled “Omni-ChannelProductDistribution NetworkDesign byUsing the ImprovedParticle Swarm Optimization Algorithm” construct the jointrandomization planning model of location and routing forthe minimization of total cost of a supply chain distributionnetwork under uncertain customer demand.

�e paper entitled “Analysis of Signal Game for SupplyChain Finance (SCF) of MSEs and Banks Based on Incom-plete Information Model” by Z. Tao et al. uses a signalgaming model based on incomplete information to analyzethe decisions of commercial banks and medium-size andsmall enterprises (SMEs) in supply chain finance business,and concludes that the returns of banks are closely relied onthe probability of good SMEs join in supply chain financebusiness and the default cost is an important constraint fordetermining the strategies adopted by both SMEs and banks.

�e paper by J. Hao et al. entitled “Bilevel ProgrammingModel of Urban Public Transport Network under FairnessConstraints” presents a bilevel programming model of thepublic transport network considering factors such as the percapita occupancy area and travel cost of different groups toalleviate the urban transportation equity and optimize the

HindawiDiscrete Dynamics in Nature and SocietyVolume 2019, Article ID 3597314, 5 pageshttps://doi.org/10.1155/2019/3597314

2 Discrete Dynamics in Nature and Society

urban public transport network under fairness constraints.�e upper layer minimizes the travel cost deprivation coef-ficient and the road area Gini coefficient by taking intoaccount fairness constraints; the lower layer models theselection behavior of different groups in the optimal schemeobtained at the upper layer as a stochastic equilibriumtraffic assignment problem with multimode and multiuser.An improved genetic algorithm is developed to solve theconstructed model and is validated via a simple network.�e experimental results show that the current model canimprove significantly the transportation equity feeling of low-income groups, reduce the overall travel time via publictransport network, and thus attract more high and middleincome users who owned cars to use the public transportnetwork.

S. Chen and C.Wang in the paper entitled “Incorporatinga Bayesian Network into Two-Stage Stochastic Programmingfor Blood Bank Location-Inventory Problem in Case ofDisasters” construct a Bayesian Network to describe a bloodlogistics network considering uncertainties and interdepen-dences caused by earthquakes. A two-stage multiperiodstochastic programming model is developed where the firststage focuses on blood bank location and inventory planningproblem and the second stage is composed of multipleperiods, some of which may suffer disasters and initiatecorresponding rescue operations.

�e paper entitled “Evaluating the Spatial Deprivation ofPublic Transportation Resources in Areas of Rapid Urban-ization: Accessibility and Social Equity” by C. Han et al.introduces an evaluation system with six indexes to evaluatethe spatial differentiation of public transportation resourcesand services. SPSS is applied to analyze the data collectedfrom a typical rapid urbanization area in China and twomainfactors are shown to have significant impact on the spatialdeprivation associated with public transportation resourcesand services.�e authors conclude that the public transporta-tion situation in rapid urbanization areas is consistent withthe local land-use context and the methods applied in thisstudy are suitable for extracting spatial public transportationcharacteristics.

�e paper by L. Huang et al. entitled “Discrete Optimiza-tion Model and Algorithm for Driver Planning in PeriodicDriver Routing Problem” presents a mixed-integer linearprogramming model for a periodic driver routing problemwith an objective of minimizing the total workload by takinginto account the relationship between workload differentialamong drivers and total workload. A local branching basedmethod is developed to solve large instances of the problemand numerical experiments are conducted to validate theeffectiveness and efficiency of the proposed model andsolution method, as well as the effect of small workloaddifferential among drivers on the total workload.

Y. Liu et al. in the paper entitled “Research on theScheduling Problem of Movie Scenes” consider the factorsaffecting the cost of movie scenes shooting in the realworld and construct an integer linear programming modelfor the scheduling of the movie sense with an objective ofminimizing the total cost. �e constructed model is solvedby a Tabu search based method (TSBM) and a particle swarm

optimization basedmethod (PSOBM). Both of thesemethodsare verified to be suitable for solving small-scale problemswhile the former is shown to be more efficient in solving thelarge-scale problem according to the experimental results.

�e paper entitled “Simulation Optimization of DiscreteLogistics Processes: A Case Study on Logistics of an E-Commerce Enterprise in Shanghai” by X. Xu et al. introducesthe simulation of the logistics distribution process of an E-commerce enterprise in Shanghai with AnyLogic So�ware tooptimize the targeted system from three aspects, includingroutes selection, warehouses quantity, andwarehouses layout.�e results of this study can provide valuable references forpractical logistics of similar E-commerce enterprise.

Y. Chen et al. in the paper entitled “Pricing Decisions onReward-Based Crowdfunding with Bayesian Review SystemFacing Strategic Consumers” extend the research on theoptimal pricing decision with review system for the reward-based crowdfunding. Firstly, a Bayesian analysis is establishedto construct consumers’ belief update process in presenceof review system. Secondly, the strategy without the reviewsystem is taken as a benchmark to explore the impacts ofreview system under preannounced pricing and responsivepricing. It is found, through the equilibrium analysis, thatthe review system has positive impact on the creator underresponsive pricing policy and the fraction of favorable reviewhas a large effect on the profit of preannounced pricing.

�e paper entitled “Research on Supply Chain Coor-dination Based on Block Chain Technology and CustomerRandom Demand” by Y. Li et al. focuses on supply chaincoordination under the combined effects of block chaintechnology and randomdemand. Firstly, both a decentralizedand a centralized supply chain decision model are built ina single-cycle newsvendor random demand situation. �en,through revenue sharing contract the study designs a brand-new supply chain coordination model which is Del trust,decentralized, and traded anonymously. According to thenumerical comparative analysis on the optimal decision andsupply chain coordination, it is found that the whole supplychain revenue can achieve and even exceed the performancelevel of the centralized supply chain with effectively expand-ing sales market and reducing supply chain risk. When theretail price is stable and supply chain is coordinated withrevenue sharing mechanism, decentralized supply chain canachieve minimum optimal revenue. Coordination resultshave effect on short-term revenues of block chain membersonly.

�e paper by L. Ma et al. entitled “Adopting a QCAApproach to Investigating the Risks Involved in Megapro-jects from Auditing Perspective” introduces the microscopicempirical analysis on twenty-two typical cases by adoptingthe quality comparative analysis (QCA) from the audit-ing perspective. �e results reveal that there is complexmultiple concurrent causation among eight conditions, andthe configuration of those conditions can be divided intosix types, three of which, namely, the project managementrisk, preliminary and construction risk, and tendering andcontract management related risk, are almost eighty percent.�e analysis further reveals that megaproject risks in Chinaare caused by complicated and changeable combination

Discrete Dynamics in Nature and Society 3

conditions, providing a new breakthrough for the researchersand practitioners to control the megaproject risks from amore systematic way.

�e paper entitled “A Metaheuristic Algorithm to Trans-porter Scheduling for Assembly Blocks in a Shipyard con-sidering Precedence and Cooperating Constraints” by N.-R.Tao et al. considers an optimization transporter schedulingproblem for assembly blocks in shipyards with an objective ofminimizing logistics time, which includes empty travel timeof transporters andwaiting time and delay time of block tasks.Amathematical model is constructed by considering the timewindows of ship blocks, carrying capacity of transporters,and precedence relationships of tasks and is solved by ametaheuristic algorithm based on the hybrid topologicalgraph, genetic algorithm, and Tabu search. �e results showthe efficiency and effectiveness of the proposed algorithmcompared to the optimal results in small-size instances andseveral strategies in large-scale instances.

�e paper entitled “Distance-Based Congestion Pricingwith Day-to-Day Dynamic Traffic Flow Evolution Process”by Q. Cheng et al. describes the distance-based congestionpricing in a network considering the day-to-day dynamictraffic flow evolution process with a mini-max regret modelto optimize the worst condition among the whole planningperiod and ameliorate severe traffic congestions in some baddays. Firstly, a piecewise linear function is adopted to formu-late the nonlinear distance toll, which can be encapsulatedto a day-to-day dynamics context. �en, a logit-type Markovadaptive learning model is proposed to depict commuters’day-to-day route choice behaviors. Finally, a robust opti-mization model which minimizes the maximum total travelcost among the whole planning horizon is formulated and amodified artificial bee colony algorithm is developed for therobust optimization model.

S. Qin et al. in the paper entitled “Applying Big DataAnalytics to Monitor Tourist Flow for the Scenic AreaOperation Management” use the big data technology andCall Detail Record (CDR) data with the mobile phone real-time location information to monitor the tourist flow andanalyze the travel behavior of tourists in scenic areas. Bycollecting CDR data and implementing a modeling analysisof the data to simultaneously reflect the distribution oftourist hot spots in Beijing, tourist locations, tourist origins,tourist movements, resident information, and other data,the results provide big data support for alleviating trafficpressure at tourist attractions and tourist routes in the cityand rationally allocating traffic resources. �e analysis showsthat the big data analysis method based on the CDR dataof mobile phones can provide real-time information abouttourist behaviors in a timely and effective manner. �isinformation can be applied for the operation management ofscenic areas and can provide real-time big data support for“smart tourism”.

Y. Peng et al. in the paper entitled “An Improved GeneticAlgorithm Based Robust Approach for Stochastic DynamicFacility Layout Problem” deal with stochastic dynamic facil-ity layout problem under demand uncertainty in termsof material flow between facilities with the considerationof transport device management. An improved adaptive

genetic algorithm with population initialization strategy isdeveloped to reduce the search space and improve the solvingefficiency. �e effectiveness of the proposed algorithm isverified by comparing it with particle swarm optimization(PSO) algorithm, and the experimental results show the goodperformance of the robust layout compared to the expectedlayout.

�e paper by H. Fei and C. Zhang entitled “Optimizingthe Composite Cost Involved in Road Motor-TransportingTrucks by Taking into Account Traffic Condition” focuses onthe planning of road motor-transporting services by takinginto account road traffic condition, especially for urban areaswith an objective ofminimizing the composite cost, includingboth the economic cost related to the driver cost and fuelconsumption, and the social cost related to the vehicleemissions. �e dynamic road traffic condition is imitateddynamically with a discretization technique. Ametaheuristicis applied with data collected from a dense district in a hugecity. Experimental results show that the proposed approachcan always converge quickly to the best solution and thesolution with minimal composite cost can always dominatethe other solutions with classic route optimization goals.

�e paper entitled “Optimal Scheme for Process Qualityand Cost Control by Integrating a Continuous Sampling Planand the Process Yield Index” by C. Li et al. presents thedevelopment of an optimal scheme for process quality andcost control to monitor the process cost and improve theprocess quality by taking into account four parameters: clear-ance number, inspecting fraction, sample size, and criticalvalue. �e Continuous Sampling Plan and the Process YieldIndex are integrated to improve the output of the schemeand a case study is illustrated to validate the effectiveness andpracticality of the proposed scheme.

P. Zhang and G. Liu in the paper entitled “Data-DrivenRecovery Potential Analysis and Modeling for BatteriesRecovery Operations in Electric Bicycle Industry” estimatethe annual waste quantity of lead-acid batteries used inelectric bicycles in 2000-2022 using the “market supply Amodel” and the “Stanford Model”, respectively. Based on theproportion of raw materials contained in lead-acid batteriesand the proportion between reclaimed and discarded lead-acid batteries, the authors estimate the recovery potential ofsuch batteries in 2000-2022.�e research data and results canhelp decision-makers make more effective andmore accuratemanagement measures and policies.

�e paper entitled “Implementation Flexibility of Multi-period Rail Line Design with Consideration of Uncertaintiesin Population Distribution” by K. Zhang et al. introduces theinvestigation results related to the implementation flexibilityof multiperiod rail line design in a linear monocentriccity. �ree alternatives (fast-tracking, deferring, and do-nothing-alternative (DNA) of a candidate rail line project) areexamined, based on an in-depth uncertainties analysis of thedemand side for this candidate rail line project. Conditionsfor the three alternatives of fast-tracking, deferring, andDNA are analytically explored and an illustrative exampleis given to demonstrate the application of the proposedmodels. Insightful findings are reported on the interrelation-ship between the rail line length and spatial and temporal

4 Discrete Dynamics in Nature and Society

correlation of population distribution as well as the impli-cation of the correlation in practice. Sensitivity analyses arecarried out in several scenarios in another numerical exampleto show the proposed conditions of the three alternatives.

�e paper by H. Hu et al. entitled “Optimization of Vehi-cle Routing with Pickup Based on Multibatch Production”suggests a mixed-integer programming model for the jointoptimization of multibatch production and vehicle routingproblems involving a pickup to reduce both transportationand inventory cost.�e targeted problem is solved within twostages. In the first stage, an integrated algorithm, combiningthe Clarke-Wright (CW) algorithm and the Record to Record(RTR) travel algorithm, is developed to solve vehicle routingproblem. In the second stage, the particle swarmoptimization(PSO) algorithm is proposed to allocate vehicles to eachproduction batch. Multiple sets of numerical experiments areperformed to validate the effectiveness of the proposedmodeland the performance efficiency of this two-stage hybridalgorithm.

Q. Wang et al. in the paper entitled “Integrated Opti-mization on Assortment Packing and Collaborative Shippingfor Fashion Clothing” construct an integrated optimizationproblem that combines fashion clothing assortment packingwith collaborative shipping simultaneously. A simplifiedmodel is then derived from the original model and solved bya commercial programming solver. Numerical results showthat the proposed model is beneficial to the fashion clothingassortment packing and collaborative shipping planning.

�e paper entitled “Optimal Strategies for Manufacturerswith the Reference Effect under Carbon Emissions-SensitiveRandom Demand” by B. Zhang et al. proposes the optimalstrategies for a newsvendor system with joint reference effect,carbon emissions-sensitive random demand, and strategiccustomers’ behavior, with the purpose of determining theselling price, production quantity, and carbon emissionsunder exogenous and endogenous price cases, respectively.How the loss aversions affect the newsvendor’s decisions isexplored and the study concludes that the newsvendor hasa uniquely optimal policy. Furthermore, the results showthat the influence of the reference effect makes the finaldecisions deviate from the optimal solutions of the classicalmodel and that the loss aversions have a great impact on thenewsvendor’s decisions.

�e paper byC.Ma et al. entitled “AMultiobjective RouteRobust Optimization Model and Algorithm for HazmatTransportation” introduces a multiobjective robust optimiza-tion model for the routing optimization problem of haz-ardous materials transportation in uncertain environmentby applying the Bertsimas-Sim robust optimization theory.A fuzzy C-means clustering-particle swarm optimization(FCMC-PSO) algorithm is designed, where the FCMC algo-rithm is used to cluster the demand points and the PSOalgorithm with the adaptive archives grid is applied to calcu-late the robust optimization route of hazmat transportation.�e numerical results verify the effectiveness of the proposedmethod and this study can provide basic theory support forhazmat transportation safeguarding.

J. Liu et al. in the paper entitled “Hydrological LayeredDialysis Research on Supply Chain Financial Risk Prediction

under Big Data Scenario” construct a supply chain financialrisk prediction method under big data by drawing on the riskmanagement theory in economics and the distributed hydro-logical model in hydrology. First, a “hydrological database”is built for the risk analysis of supply chain financing underbig data. Second, the risk identification models of “watercircle model”, “surface runoff model”, and “undergroundrunoff model” are applied to carry on the risk predictionfrom the overall level (water circle). Finally, the supply chainfinancial risk analysis from breadth level (surface runoff) anddepth level (underground runoff) is performed. �e resultsof this study can enrich the research on risk management ofsupply chain finance and provide feasible and effective riskpredictionmethods and suggestions for financial institutions.

H. Hu et al., in the paper entitled “A MetaheuristicMethod for the Task Assignment Problem in Continuous-Casting Production”, focus on the task assignment problemin the downstream stage within the given information result-ing from the upstream stage involved in the steelmakingand continuous-casting process in integrated iron and steelenterprises. A nonlinear mixed-integer programming modelis constructed, with an objective of minimizing the totaltardiness within the resource constraints and time windowsconstraints for the tasks, and is solved by an improvedsolution algorithm based on particle swam optimization.

�e paper by Y. Wei et al. entitled “Inventory andProduction Dynamics in a Discrete-Time Vendor-ManagedInventory Supply Chain System” analyzes production andorder dynamics in the context of a discrete-time VMI supplychain system composed of one retailer and one manufac-turer. �e authors firstly derive the lower bound and upperbound on the range of inventory fluctuations for the retailerunder unknown demand and prove that the productionfluctuations can be interestingly smoothed and stabilizedindependently of the delivery frequency of the manufacturerused to satisfy the retailer’s demand, even if the retailersubsystem is unstable. �e sufficient and necessary stabilitycondition for the whole supply chain system is obtained,and the bullwhip effect under unknown demand is furtherexplored based on a transfer functionmodel with the purposeof disclosing the influences of parameters on productionfluctuations. All the theoretical results derived with respectto inventory and production fluctuations are validated bysimulation experiments.

�e paper entitled “Dynamic Strategies on Firm Pro-duction and Platform Advertisement in Crowdfunding con-sidering Investor’s Perception” by Y. Ji et al. introduces adynamic decision model for film investment by taking intoaccount the effects of information about product quality andplatform advertisement on the investor’s perception. Firstly,investment desire and reference price of the investor areintroduced in two dynamic settings to describe investor’sperception. �en, the optimal decisions about the productquality and platform advertisement are formulated undertwo circumstances: the sponsor and the platform makedecisions independently and they cooperate as a system.Finally, the influences of reference price and cost-sharingratio on the optimal results are compared and the datasimulation experiment verifies the necessity of the study.

Discrete Dynamics in Nature and Society 5

J. Feng and B. Liu, in the paper entitled “Goodwill andSystem Dynamics Modeling for Film Investment Decisionby Interactive Efforts”, develop a goodwill model and systemdynamic (SD)model to optimize the film investment decisionconsidering advertising, film-making, and power of stars.�eresults show that advertising has great impact on absorbingmoviegoers’ attention, investing in film-making should beemphasized when film quality has a great impact on themovie's reputation and audience's viewing decision, and thefilm producer should pay more attention to the higher cost-performance stars who have more reasonable remuneration,better acting skills, and bigger box-office guarantee. It can alsobe concluded that rational audience contribute more thanfans to a movie's box-office, bankable stars contribute morethan high-profile stars to amovie's returns, and the film seriesyields higher profits thannew thememovies although the costof investment is the same.

�e paper by D. Huang et al. entitled “An IncentiveDynamic Programming Method for the Optimization ofScholarship Assignment” proposes an incentive methodinspired by dynamic programming to find the optimal schol-arship assignment scheme with the highest equity consider-ing both the practical constraints and the equity requirement.In order to assign the scholarship avoiding time- and energy-consuming application processes conducted by students,feasible assignment schemes are generated by iterativelysolving a series of knapsack subproblems based on dynamicprogramming and adjusting the monetary value of a unitscore, and then the optimal solution will be screened outby applying the Gini coefficient for quantifying the equity ofeach feasible scheme. �e numerical results indicate that theproposed method is an efficient tool to assign scholarships tostudents with consideration of the equity.

�e paper entitled “Optimizing Price of Credit DefaultSwaps for Dynamic Project System of Public-Private Partner-ship” by M. Wu et al. introduces a method for optimizingthe price of credit default swaps (CDS) for the dynamic PPPsystem. �is study investigates the credit risk measurementof PPP project financing and the pricing of risk mitigationinstruments which are widely used in the case of immaturemarkets in the early stage of China’s PPP development. Basedon the credit risk measurement theory of the corporateand debt ratings, this paper considers the differences invarious credit enhancement methods in the equity-like debtagreement and determines the credit rating of the equity-like debt in PPP projects. Some optimization methods arealso proposed to derive the probability of default, so as todetermine the price of the credit risk mitigation instrumentof CDS which is based on the equity-like debt.

�e paper entitled “Complexity Analysis of DynamicCooperativeGameModels for Supply Chainwith the Reman-ufactured Products” by J. Chang and L. Zhao suggestscoupling dynamics of the forward supply chain of Stackelberggamemodel constructed for the supply chain within remanu-facturing production system composed of one manufacturerand one retailer, where the manufacturer is responsible forthe production of both new products and remanufacturedproducts. A�er performing experiments designed by takinginto account some dynamic phenomena such as bifurcation

and chaos, the authors conclude that the equilibrium of thesystem can lose stability via flip bifurcation or Neimark-Sacker bifurcation and that time-delayed feedback control isappropriate for stabilizing the chaotic behaviors of the system.

We believe that the special issue will provide usefulreferences for the researchers and practitioners working inthe discrete optimization for dynamic systems of operationsmanagement in data-driven society.

Conflicts of Interest

�e editors declare that they have no conflicts of interestregarding the publication of the special issue.

Acknowledgments

�e guest editorial team would like to express gratitude to allthe authors for their interest in selecting this special issue asa venue for disseminating their scholarly work. �e editorsalso wish to thank the anonymous reviewers for their carefulreading of the manuscripts submitted to this special issue andtheir many insightful comments and suggestions.

Lu ZhenShuaianWang

Xiaobo QuXinchang Wang

Hindawiwww.hindawi.com Volume 2018

MathematicsJournal of

Hindawiwww.hindawi.com Volume 2018

Mathematical Problems in Engineering

Applied MathematicsJournal of

Hindawiwww.hindawi.com Volume 2018

Probability and StatisticsHindawiwww.hindawi.com Volume 2018

Journal of

Hindawiwww.hindawi.com Volume 2018

Mathematical PhysicsAdvances in

Complex AnalysisJournal of

Hindawiwww.hindawi.com Volume 2018

OptimizationJournal of

Hindawiwww.hindawi.com Volume 2018

Hindawiwww.hindawi.com Volume 2018

Engineering Mathematics

International Journal of

Hindawiwww.hindawi.com Volume 2018

Operations ResearchAdvances in

Journal of

Hindawiwww.hindawi.com Volume 2018

Function SpacesAbstract and Applied AnalysisHindawiwww.hindawi.com Volume 2018

International Journal of Mathematics and Mathematical Sciences

Hindawiwww.hindawi.com Volume 2018

Hindawi Publishing Corporation http://www.hindawi.com Volume 2013Hindawiwww.hindawi.com

The Scientific World Journal

Volume 2018

Hindawiwww.hindawi.com Volume 2018Volume 2018

Numerical AnalysisNumerical AnalysisNumerical AnalysisNumerical AnalysisNumerical AnalysisNumerical AnalysisNumerical AnalysisNumerical AnalysisNumerical AnalysisNumerical AnalysisNumerical AnalysisNumerical AnalysisAdvances inAdvances in Discrete Dynamics in

Nature and SocietyHindawiwww.hindawi.com Volume 2018

Hindawiwww.hindawi.com

Di�erential EquationsInternational Journal of

Volume 2018

Hindawiwww.hindawi.com Volume 2018

Decision SciencesAdvances in

Hindawiwww.hindawi.com Volume 2018

AnalysisInternational Journal of

Hindawiwww.hindawi.com Volume 2018

Stochastic AnalysisInternational Journal of

Submit your manuscripts atwww.hindawi.com