9052

8397

كارشناسي ارشد

صنايع

اصفهان: دانشگاه صنعتي اصفهان، دانشكده صنايع و سيستم ها

1392

يازده،90ص.: مصور،جدول،نمودار

ص.ع.به فارسي و انگليسي

مهدي بيجاري

26/3/93

قاسم مصلحي، محمد سعيد صباغ

مهندسي صنايع و سيستم ها

ID8397

Robust Simultaneous Lot sizing Scheduling model Mahboobeh Kabiri Zamani m kabii@in iut ac ir Date of Submission 2014 01 22 Department of Industrial Engineering Isfahan University of Technology Isfahan 84156 83111 Iran Degree M Sc Language FarsiSupervisor Dr Mehdi Bijari bijari@cc iut ac irAbstractReducing production costs has become one of the most important concerns due to the economicdevelopment and increasing competitiveness in industries To achieve this goal considering real conditionsis important On the other side the main goal of the most companies is trying to fulfill the needs of theircustomers without spending a lot of time Optimization models have been used to support decision makingin production planning However several of those models are deterministic and do not address thevariability that is present in some of the data Robust Optimization is a methodology which can deal withthe uncertainty or variability in optimization problems by computing a solution which is feasible for allpossible scenarios of the data within a given uncertainty set Simultaneous Lot sizing Scheduling is animportant problem in production planning environments In this thesis a model similar to traveling salesmanproblem with uncertain demand is presented The problem objective is to determine the production lot sizesand their schedules in order to minimize the sum of the total setup cost total holding cost and totalbackorder cost Two robust optimization criterions are applied to formulate a robust linear programmingmodel The first model considering deviation from optimal and shortage cost The second model is basedon worst case criterion that can adjust different risks for decision makers Finally we provide a set ofnumerical examples for 1000 small scale problem to verify the effectiveness of the approaches Since themodel could not solve the NP hard large size problems two heuristic Fix Relax algorithms are used tosolve this group of problems Then the efficiency of these algorithms in different groups of problemsevaluated Experimental results that among 900 large scale problems show that the first method is better inaverage time and the second method has lower average error The average errors of these two algorithmsare 4 89 and 3 12 for the first robust model and 2 35 and 1 55 for the second robust model respectively Keywords Scheduling Lot sizing Robust optimization Scenario based approach Rolling horizon

مهدي بيجاري

قاسم مصلحي، محمد سعيد صباغ