

Articles
by
M. Zandieh 
Total Records (
9 ) for
M. Zandieh 





M. Zandieh
and
S. Molla AlizadehZavardehi


In this study, for coordination of production and distribution
scheduling in the implementation of a supply chain solution, we studied
the problem of synchronized scheduling of single machine and air transportation
in supply chain management. The overall problem is decomposed into two
subproblems, which consists of air transportation allocation problem
and a single machine scheduling problem which they are considered together.
We have taken into consideration different constraints and assumptions
in our modeling such as due window, delivery tardiness and no delivery
tardiness. For these purposes, mathematical models have been proposed
to minimize supply chain total cost which encompasses transportation,
makespan, delivery earliness tardiness and departure time earliness tardiness
costs. 




B. Vahdani
,
M. Zandieh
and
A. AlemTabriz


In this study, Multiple Criteria Decision Model (MCDM)
is used for optimization of several conflicting criteria dependent systems.
A MCDM approach taking into account the performance defining attributes
such as profitability of supplier, relationship closeness, technological
capability, conformance quality and conflict resolution, was adopted to
determine the performance ranking of suppliers. It is a threestepped
procedure to derive an overall complete final order of the suppliers.
The outranking matrix is derived, indicating the frequency of the relative
superiority of suppliers with respect to each other based on each criterion.
The outranking matrix is triangularised to obtain an implicit ordering
or provisional order of suppliers, based on sequential application of
a balancing principle supported by the pair wise comparison of the suppliers
with the help of advantagesdisadvantages table. 




M. Amiri
,
M. Zandieh
,
B. Vahdani
,
M. Yazdani
and
R. Soltani


In this study, we present a hybrid MultiCriteria Decision
Making (MCDM) model to solve convention site selection. In the proposed
model, interval comparison matrix which has been inspired by Analytical
Hierarchy Process (AHP) is employed to compare the criteria against each
other. Furthermore, to calculate the interval weights of criteria, we
make use of Goal Programming (GP). Moreover, interval data is utilized
to evaluate the alternatives with respect to the criteria. In order to
rank the alternatives with respect to criteria, technique for order preference
by similarity to an ideal solution (TOPSIS) with interval data and weights
is used. In the conditions where there exist uncertainties for both the
comparison of criteria against each other and alternatives evaluation
with respect to influential criteria in the process of decision making,
using this model facilitates the decision making process and causes the
quality of decision will be enhance. 




M. Zandieh
,
I. Mahdavi
and
A. Bagheri


A metaheuristic approach for solving the flexible jobshop scheduling problem (FJSP) is presented in this study. This problem consists of two subproblems, the routing problem and the sequencing problem and is among the hardest combinatorial optimization problems. We propose a Genetic Algorithm (GA) for the FJSP. Our algorithm uses several different rules for generating the initial population and several strategies for producing new population for next generation. Proposed GA is tested on benchmark problems and with due attention to the results of other metaheuristics in this field, the results of GA show that our algorithm is effective and comparable to the other algorithms. 




M. Zandieh
,
A. Azadeh
,
B. Hadadi
and
M. Saberi


This study presents an integrated Artificial Neural
Networks (ANN) to estimate and predict airline number of passenger in
Iran. All type of ANNMulti Layer Perceptron (MLP) is examined to this
estimation. The ANN models are implemented on MATLAB software. AutoCorrelation
Function (ACF) is utilized to define input variables. Finally, the best
type of ANNMLP is determined with Data Envelopment Analysis (DEA). KruskalWallis
test is used for asses the impact of raw data, preprocessed data and post
process method on ANN performance. Monthly airline number of passenger
of Iran airline from 1993 to 2005 is considered as the case of this study. 




M.B. Abiri
,
M. Zandieh
and
A. AlemTabriz


This study describes a Tabu Search (TS) algorithm approach
to the scheduling of a sequencedependent setup times hybrid flow shop.
The details of a TS approach are described and implemented. The results
obtained are compared with those computed by Random Key Genetic Algorithm
(RKGA) presented earlier. From the results, it was established that TS
outperformed RKGA. 




M. Zandieh
,
F. Jolai
,
S.M.T. Fatemi Ghomi
and
M. Mirabi


This study investigate the permutation flowshop scheduling
problem in which there are sequence dependent setup times on each machine,
commonly known as the SDST flowshop. The optimization criteria considered
is the minimization of the makespan or C_{max}. Many heuristics
and metaheuristics have been successfully applied to this kind of problem
before like genetic algorithm, tabu search and greedy algorithm and the
objective of this study is to assess their effectiveness in a more realistic
and complex environment. We present a hybrid electromagnetismlike (HEM)
algorithm for the permutation flowshop scheduling with sequence dependent
setup times that have shown superior performance against other metaheuristics
when applied to proposed problem. The proposed HEM algorithm benefits
of a new concept named priority assigning to calculate electrostatic force
and also it implements a new formulation for solution charge. Using a
good approach for acquiring the initial solutions and also some effective
local searches to finding neighborhood solutions are other novelties of
the HEM. For evaluating the proposed algorithm we have coded several wellknown
algorithms for SDST flowshop. All methods including HEM are tested on
the randomly instances and results indicate that HEM is very competitive
with the existing bestperforming algorithms. 




M. Yazdani
,
M. Gholami
,
M. Zandieh
and
M. Mousakhani


This study addresses the flexible jobshop scheduling
problem to minimize makespan. In fact, the FJSP mainly presents two difficulties.
The first one is to assign each operation to a machine out of a set of
capable machines and the second one is to sequence the assigned operations
on all machines. Hence, to solve this NPhard problem, a simulated annealing
algorithm is proposed. The metaheuristic algorithm explores the solution
space using a stochastic local search while trying to avoid local optima
through accepting probabilistic moves to the worse solutions. The neighborhood
search structures of assignment and sequencing are used for generating
neighboring solutions to search the solution space. To evaluate the performance
of the algorithm, twenty benchmark problems adopted from the literature
are used. Consequently, the computational results validate the quality
of present approach. 




A. Alem Tabriz
,
M. Zandieh
and
Z. Vaziri


This study deals with the hybrid flow shop scheduling problems in which there are sequencedependent setup times. This type of production system is found in industries such as chemical, textile, metallurgical, printed circuit board and automobile manufacture. This study describes a simulated annealing algorithm to the scheduling of a hybrid flow shop with sequencedependent setup times. The obtained results are compared with those computed by RKGA presented previously. The superiority and effectiveness of our novel simulated annealing algorithm is inferred from all the results obtained in various situations. 





