2021-12-04T08:15:42Z
http://www.qjie.ir/?_action=export&rf=summon&issue=20
Journal of Optimization in Industrial Engineering
JOIE
2251-9904
2251-9904
2012
5
10
Analysing Price, Quality and Lead Time Decisions with the Hybrid Solution Method of Fuzzy Logic and Genetic Algorithm
amin
mahmoudi
hassan
shavandi
khashayar
nouhi
In this paper, the problem of determining the quality level, lead time for order delivery and price of a product produced by a manufacturer is considered. In this problem the demand for the product is influenced by all three decision variables: price, lead time and quality level. To formulate the demand function, a fuzzy rule base that estimates the demand value based on the three decision variables is developed. To doso, the linguistic knowledge of experts in the form of if-then rules is used to establish the fuzzy system. Moreover, in order to solve the problem, a genetic algorithm integrating the fuzzy rule base is proposed. Finally, to support the validity of the proposed solution, a numerical study is provided.
Fuzzy Logic
Linguistic variable
Genetic Algorithm
Pricing
Quality level
Lead time
2012
03
15
1
9
http://www.qjie.ir/article_111_6154acbc18e93f5b9cc40af04d427abf.pdf
Journal of Optimization in Industrial Engineering
JOIE
2251-9904
2251-9904
2012
5
10
A Neural Network Model Based on Support Vector Machine for Conceptual Cost Estimation in Construction Projects
Behnam
Vahdani
Seyed Meysam
Mousavi
Morteza
Mousakhani
Mani
Sharifi
Hassan
Hashemi
Estimation of the conceptual costs in construction projects can be regarded as an important issue in feasibility studies. This estimation has a major impact on the success of construction projects. Indeed, this estimation supports the required information that can be employed in cost management and budgeting of these projects. The purpose of this paper is to introduce an intelligent model to improve the conceptual costaccuracy during the early phases of the life cycle of projects in construction industry. A computationally efficient model, namely support vector machine model, is developed to estimate the conceptual costs of construction projects. The proposed neural network model is trained by a cross validation technique in order to produce the reliable estimations. To demonstrate the performance of the proposed model, twopowerful intelligent techniques, namely nonlinear regression and back-propagation neural networks (BPNNs), are provided. Their results are compared on the basis of the available dataset from the related literature in construction industry. The computational results illustrate that the presented intelligent model performs better than the other two powerful techniques.
Construction Projects
Conceptual cost estimation
Support vector machine
Cross validation
2012
03
15
11
18
http://www.qjie.ir/article_120_7935717667a6746bc50397fef1de0873.pdf
Journal of Optimization in Industrial Engineering
JOIE
2251-9904
2251-9904
2012
5
10
An Integrated Model of Project Scheduling and Material Ordering: A Hybrid Simulated Annealing and Genetic Algorithm
Nima
Zoraghi
Amir Abbas
Najafi
Seyed Taghi
Akhavan Niaki
This study aims to deal with a more realistic combined problem of project scheduling and material ordering. The goal is to minimize the total material holding and ordering costs by determining the starting time of activities along with material ordering schedules subject to some constraints. The problem is first mathematically modelled. Then a hybrid simulated annealing and genetic algorithm is proposed tosolve it. In addition, some experiments are designed and the Taguchi method is employed to both tune the parameters of the proposed algorithm and to evaluate its performance. The results of the performance analysis show the efficiency of the proposed methodology.
Project Scheduling
Material ordering
Hybrid simulated annealing
Taguchi design
2012
03
15
19
27
http://www.qjie.ir/article_96_00e403c295624f6424205f6aae2e41f6.pdf
Journal of Optimization in Industrial Engineering
JOIE
2251-9904
2251-9904
2012
5
10
Sensitivity Analysis in the QUALIFLEX and VIKOR Methods
Alireza
Alinezhad
Nima
Esfandiari
The sensitivity analysis for multi-attribute decision making (MADM) problems is important for two reasons: First, the decision matrix as the source of the results of a decision problem is inaccurate because it sorts the alternatives in each criterion inaccurately. Second, the decision maker may change his opinions in a time period because of changes in the importance of the criteria and in the policy of the organization over time. This in turn makes problem solving really time-consuming. Therefore, the best solution is to do sensitivity analysis.In this regard, this paper considers a sensitivity analysis in the QUALIFLEX method which is a compromise ranking method used for multi-criteria decision making (MCDM).
Sensitivity analysis
QUALIFLEX
VIKOR
Multi-criteria decision making
Multi-attribute Decision Making
2012
03
15
29
34
http://www.qjie.ir/article_79_e63c5ae3e67369dc281eef944aa62a3a.pdf
Journal of Optimization in Industrial Engineering
JOIE
2251-9904
2251-9904
2012
5
10
Design of a Mathematical Model for Logistic Network in a Multi-Stage Multi-Product Supply Chain Network and Developing a Metaheuristic Algorithm
Esmaeil
Mehdizadeh
Fariborz
Afrabandpei
Logistic network design is one of the most important strategic decisions in supply chain management that has recently attracted the attention of many researchers. Transportation network design is then one of the most important fields of logistic network. This study is concerned with designing a multi-stage and multi-product logistic network. At first, a mixed integer nonlinear programming model (MINLP) is formulated that minimizes transportation and holding costs. Then, a hybrid priority-based Genetic Algorithm (pb-GA) andsimulated annealing algorithm (SA) is developed in two phases to find the optimal solution. The solution is represented by a matrix and a vector. Response Surface Methodology (RSM) is also used to adjust the significant parameters of the algorithm. Finally, several test problems are generated which show that the proposed metaheuristic algorithm can find good solutions in reasonable time spans.
Transportation network
Supply chain management
Metaheuristic Algorithms
Priority-based Genetic Algorithm
2012
03
15
35
43
http://www.qjie.ir/article_121_01265540a472150d8c53eba781705fc3.pdf
Journal of Optimization in Industrial Engineering
JOIE
2251-9904
2251-9904
2012
5
10
A Simulated Annealing Algorithm within the Variable Neighbourhood Search Framework to Solve the Capacitated Facility Location-Allocation
Problem
Ragheb
Rahmaniani
abdosalam
Ghaderi
Mohammad
Saidi Mehrabad
In this study, we discuss the capacitated facility location-allocation problem with uncertain parameters in which the uncertainty is characterized by given finite numbers of scenarios. In this model, the objective function minimizes the total expected costs of transportation and opening facilities subject to the robustness constraint. To tackle the problem efficiently and effectively, an efficient hybrid solution algorithm based on several meta-heuristics and an exact algorithm is put forward. This algorithm generates neighborhoodsby combining the main concepts of variable neighborhood search, simulated annealing, and tabu search and finds the local optima by using an algorithm that uses an exact method in its framework. Finally, to test the algorithms’ performance, we apply numerical experiments on both randomly generated and standard test problems. Computational experiments show that our algorithm is more effective and efficient in term of CPU time and solutions quality in comparison with CPLEX solver.
Capacitated Facility Location-allocationProblem
Single allocation
Uncertainty
Hybrid Algorithm
2012
03
15
45
54
http://www.qjie.ir/article_125_a48b3a0aee72f714d5f7da41be4a6fe8.pdf
Journal of Optimization in Industrial Engineering
JOIE
2251-9904
2251-9904
2012
5
10
An Exact Algorithm for the Mode Identity Project Scheduling Problem
Behrouz
Afshar Nadjafi
Amir
Rahimi
Hamid
Karimi
In this paper we consider the non-preemptive variant of a multi-mode resource constrained project scheduling problem (MRCPSP) with mode identity, in which a set of project activities is partitioned into disjoint subsets while all activities forming one subset have to be processed in the same mode. We present a depth-first branch and bound algorithm for the resource constrained project scheduling problem with mode identity. The proposed algorithm is extended with some bounding rules to reduce the size of branch and bound tree. Finally, some test problems are solved and their computational results are reported.
Project Scheduling
Branch and Bound
Mode-Identity
Multi-Mode
Resource Constrained
2012
03
15
55
63
http://www.qjie.ir/article_122_018f2f6dd3f3583aeca328fe93a20326.pdf
Journal of Optimization in Industrial Engineering
JOIE
2251-9904
2251-9904
2012
5
10
A Mathematical Model and a Solution Method for Hybrid Flow Shop Scheduling
Esmaeil
Najafi
Bahman
Naderi
Hassan
Sadeghi
Mehdi
Yazdani
This paper studies the hybrid flow shop scheduling where the optimization criterion is the minimization of total tardiness. First, the problem is formulated as a mixed integer linear programming model. Then, to solve large problem sizes, an artificial immune algorithm hybridized with a simple local search in form of simulated annealing is proposed. Two experiments are carried out to evaluate the modeland the algorithm. In the first one, the general performance of the model and the proposed algorithm is experimented. In the next one, the presented algorithm is compared against some other algorithms. The results support high performance of the proposed algorithm.
Scheduling
Hybrid flow shop
Mathematical model
Mixed integer linear program
Artificial immune algorithm
2012
03
01
65
72
http://www.qjie.ir/article_115_ed4deff4ed179dd35f0892b228fc9352.pdf