Adel Azar; Mahdi Abedini Naeini; Amir Afsar; Mohammad Sabet Motlagh
Volume 14, Issue 42 , October 2016, Pages 1-30
Abstract
Supplier selection and quota allocation is an important decision in supplychains. This decision can be considered as a complex multi-criteria groupdecision making problem. This decision in many practical situations is verydifficult for vague and uncertain environment. This vagueness and uncertaintycan ...
Read More
Supplier selection and quota allocation is an important decision in supplychains. This decision can be considered as a complex multi-criteria groupdecision making problem. This decision in many practical situations is verydifficult for vague and uncertain environment. This vagueness and uncertaintycan be handled by using fuzzy set theory. Therefore, this paper proposed afuzzy MCDM model to evaluate candidate suppliers and quota allocation. Ahybrid ANP-VIKOR method in fuzzy environment applied first with 16criteria to evaluate suppliers. Then, a fuzzy multi-objective mathematicalmodel is used to quota allocation. Finally, the fuzzy model is solved by Tiwarimethod. An illustration with a data set from a realistic situation is presented todemonstrate the effectiveness of the proposed model.
Akdar Alemtabriz; Ashkan Ayough; Mahdie Baniasadi
Abstract
During the recent years, extensive research has been done on the field ofproject scheduling. There is always uncertainty in the area of projectscheduling that causes a deviation in the real plan from the scheduled plan.One of the solutions to deal with this uncertainty is using the critical chainmethod ...
Read More
During the recent years, extensive research has been done on the field ofproject scheduling. There is always uncertainty in the area of projectscheduling that causes a deviation in the real plan from the scheduled plan.One of the solutions to deal with this uncertainty is using the critical chainmethod (CCM) in project scheduling. This method which is derived from thetheory of constraints (TOC) is a new method in project control which was firstproposed by Goldartt in 1997.In this research we attempt to use the principalsof critical chain in resource-constrained project scheduling problem. The maininnovation in this research is presentation of critical chain project schedulingproblem model with consideration of feeding buffer and using float as asupplement for feeding buffer. For this matter, the project scheduling underresources constraints with critical chain approach was first written and itsreliability was evaluated using the Lingo software. In the next step thesolution algorithm of this model was developed using the genetic algorithmand finally different sample issues were investigated. The results of thisresearch show the efficiency of the presented genetic algorithm
Hamidreza Shahabifard; Behrouz Afshar-nadjafi
Abstract
In this paper, a mathematical model is proposed for project portfolioselection and resource availability cost problem to scheduling activities inorder to maximize net present value of the selected projects preservingprecedence and resource constraints. Since the developed model belongs toNP-hard problems ...
Read More
In this paper, a mathematical model is proposed for project portfolioselection and resource availability cost problem to scheduling activities inorder to maximize net present value of the selected projects preservingprecedence and resource constraints. Since the developed model belongs toNP-hard problems list, so a genetic based meta-heuristic algorithm isproposed to tackle the developed model. In the proposed algorithm besidecommon operators of genetic algorithms such as crossover & mutation, someintelligent operators are utilized for local search in computed resources andshifting the activities with negative cash flows. The key parameters of thealgorithm are calibrated using Taguchi method to accelerate convergence ofthe proposed algorithm. Then, the algorithm is used to solve 90 testproblems consisting 30 small-scale, 30 middle-scale and 30 large scaleproblems to examine the algorithm’s performance. It is observed that, insmall problems, the obtained solutions from the proposed genetic algorithmhave been comparably better than the local optimum solutions stemmedfrom Lingo software. On the other hand, for the middle and large sizeproblems which there is no local optimum available within the limited CPUtime, robustness of the proposed algorithm is appropriate
Roozbeh . Azizmohammadi; Maghsoud .Amiri; Reza Tavakkoli- Moghadam; Hamid Reza. Mashatzadegan
Volume 14, Issue 42 , October 2016, Pages 103-121
Abstract
A redundancy allocation problem is a well-known NP-hard problem thatinvolves the selection of elements and redundancy levels to maximize thesystem reliability under various system-level constraints. In many practicaldesign situations, reliability apportionment is complicated because of thepresence of ...
Read More
A redundancy allocation problem is a well-known NP-hard problem thatinvolves the selection of elements and redundancy levels to maximize thesystem reliability under various system-level constraints. In many practicaldesign situations, reliability apportionment is complicated because of thepresence of several conflicting objectives that cannot be combined into asingle-objective function. A stele communications, manufacturing and powersystems are becoming more and more complex, while requiring shortdevelopments schedules and very high reliability, it is becoming increasinglyimportant to develop efficient solutions to the RAP. In this paper, a newhybrid multi-objective competition algorithm (HMOCA)based oncompetitive algorithm (CA) and genetic algorithm (GA) is proposed for thefirst time in multi-objective redundancy allocation problems. In the multiobjectiveformulation, the system reliability is maximized while the cost andvolume of the system are minimized simultaneously. Additionally, ay RSMis employed to tune the CA parameters. The proposed HMOCA is validatedby some examples with analytical solutions. It shows its superiorperformance compared to a NSGA-II and PAES algorithms. Finally, theconclusion is given
Amineh Hosseini; Kaveh Khalili-Damghani; Ali Emami Meibodi
Volume 14, Issue 42 , October 2016, Pages 123-167
Abstract
In this paper, a methodology is proposed to measure the efficiency ofnational energy sector in IRAN. The technical and environmentalperformance of the oil refineries in IRAN as a major producer of energy andfuel are evaluated based on data from years 2010 to 2013. In this study, afuzzy multi-objective ...
Read More
In this paper, a methodology is proposed to measure the efficiency ofnational energy sector in IRAN. The technical and environmentalperformance of the oil refineries in IRAN as a major producer of energy andfuel are evaluated based on data from years 2010 to 2013. In this study, afuzzy multi-objective multi-period common weight network dataenvelopment analysis approach is proposed and customized to evaluate theperformance of oil refineries. A certain scenario, called food-production inwhich a refinery is assumed as a decision making unit (DMU) consuminginputs to produce outputs, is considered to evaluate the technical andenvironmental performance in presence of undesirable outputs. The maincontribution of this study are summarized as: (1) Proposing a multiobjectivecommon weight DEA model in order to determine the weights ofinputs and outputs in a single run; (2) Calculating the long term efficiencyscores during a multiple-periods of planning incorporating dynamic natureof inputs and outputs; (3) Handling a compromise solution using fuzzymathematical programming to address multi-objective mathematicalprogramming; (4) Proposing a linear mathematical programming to achievethe global optimum solutions; (5) Enhancing the discrimination power of theDEA models; (6) Reducing the computational time of modeling and solutionprocedure; (7) incorporating effective criteria in the modeling procedure.The analysis of case study presents the efficacy and applicability ofproposed method in comparison with existing classic models.
Ali Mohamadi; Payam Shojaei; Hamid Reza Yazdani; Mohammad Reza Sadeghi Moghaddam
Abstract
Regarding to the increasing importance of supply chain risk in the lastdecade in general and projects especially, in this research the dimensions andelements of supply chain risk of projects have been determined. Therefore,Fars Gas Transfer Pipeline projects were considered to discover codes andthemes ...
Read More
Regarding to the increasing importance of supply chain risk in the lastdecade in general and projects especially, in this research the dimensions andelements of supply chain risk of projects have been determined. Therefore,Fars Gas Transfer Pipeline projects were considered to discover codes andthemes according to the phenomena by using Grounded Theory (Corbin andStrauss method). Based on final paradigm model, project supply chain riskmanagement issue was categorized in 6 main dimensions, 19 sub-dimensionsand 57 codes. The results show that supply chain risks as a core phenomenon,consists of environmental risks, organizational risks and network risks. Todo this, we use theoretical sampling and interview with 10 experts from Gasstate company and some suppliers. These interview was deep one becausewe employed open questionnaire. Then by using open encoding, axialencoding and selective encoding, paradigm model was extracted. The mainphenomenon placed the center of model and other themes joined to that
Mojtaba Heravi; Tabassom Azimi galeh; Hessam Zandhessami
Abstract
Decision making (DM) is an important problem in most of the armyoperations. One of the challenging issues in this area is uncertainty in warswith uncertain information which causes many destructive effects on theresults of strategies in battlefields. In the Heravi et al. article’s, published inthe ...
Read More
Decision making (DM) is an important problem in most of the armyoperations. One of the challenging issues in this area is uncertainty in warswith uncertain information which causes many destructive effects on theresults of strategies in battlefields. In the Heravi et al. article’s, published inthe year 2013, utilizing a combination of Cognitive Agent (CA) andClassification based on Fuzzy Association Rules (CFAR) as the mosteffective and widely used methods, was able to relatively reduce thisproblem and tried to reduce uncertainty. But still in critical condition, can’tdeny the need to act quickly and remove most invalid and inefficient rulesextracted in the effective decisions.This paper aims to utilize the capabilities of Genetic Algorithm (GA) in amore realistic selection rules as a meta-heuristic way to combinecomplementary methods to minimize the uncertainty in DM. In comparisonwith previous method, experimental results achieved, clearly show that thiscombination in addition to the advantages of the previous method, due to thefurther reduction of production rules for DM, are more understandable andaccurate and has more rational risk acceptance.
