eng
Iranian Institute of Industrial Engineering
Journal of Industrial and Systems Engineering
1735-8272
2717-3380
2016-07-01
9
3
1
16
14558
Truck scheduling problem in a cross-docking system with release time constraint
Jamal Arkat
j.arkat@uok.ac.ir
1
Parak Qods
parak.qods@gmail.com
2
Fardin Ahmadizar
f.ahmadizar@uok.ac.ir
3
Industrial Engineering Department, University of Kurdistan
Department of Industrial Engineering, University of Kurdistan
Sanandaj, University of Kurdistan, Department of Industrial Engineering
In a supply chain, cross-docking is one of the most innovative systems for ameliorating the operational performance at distribution centers. Cross-docking is a logistics strategy in which freight is unloaded from inbound trucks and (almost) directly loaded into outbound trucks, with little or no storage in between, thus no inventory remains at the distribution center. In this study, we consider the scheduling problem of inbound and outbound trucks with multiple dock doors, aiming at the minimization of the makespan. The considered scheduling problem determines where and when the trucks must be processed; also due to the interchangeability specification of products, product assignment is done simultaneously as well. Inbound trucks enter the system according to their release times, however, there is no mandatory time constraint for outbound truck presence at a designated stack door; they should just observe their relative docking sequences. Moreover, a loading sequence is determined for each of the outbound trucks. In this research, a mathematical model is derived to find the optimal solution. Since the problem under study is NP-hard, a simulated annealing algorithm is adapted to find the (near-) optimal solution, as the mathematical model will not be applicable to solve large-scale real-world cases. Numerical examples have been done in order to specify the efficiency of the metaheuristic algorithm in comparison with the results obtained from solving the mathematical model.
https://www.jise.ir/article_14558_314cd2b5606e6909af6179dd13f06cf3.pdf
cross-docking
Truck scheduling
Release time
Simulated Annealing Algorithm
eng
Iranian Institute of Industrial Engineering
Journal of Industrial and Systems Engineering
1735-8272
2717-3380
2016-07-01
9
3
17
27
14559
Multi-objective routing and scheduling for relief distribution with split delivery in post-disaster response
Fatemeh Sabouhi
s_fatemeh_3359@yahoo.com
1
Mehdi Heydari
mheydari@iust.ac.ir
2
Ali Bozorgi-Amiri
alibozorgi@ut.ac.ir
3
School of Industrial Engineering, Iran University of Science & Technology, Tehran, Iran
School of Industrial Engineering, Iran University of Science & Technology, Tehran, Iran
School of Industrial Engineering, College of Engineering, University of Tehran, Tehran, Iran
Following the occurrence of unexpected events and natural disasters, a highly important relief operation is the transferring of relief commodities from the distribution centers (CDs) to shelters. In this paper, a three-level network consisting of depot of vehicles, distribution centers and shelters has been considered for routing and scheduling of relief vehicles through introducing a multi-objectivemodel. The first objective function represents the total arrival time of vehicles to CDs and shelters. The second objective function illustrates the number of vehicles used. We use the TH method to deal with the multi-objective problem. During the relief commodities distribution, issues such as the feasibility of getting servicefrom each distribution centerwith multiple vehicles, and heterogeneous fleet of vehicles has been regarded. In order to solve the proposed model and represent its efficiency, we select the fourth region of Tehran city as a case study, run the model on it, and present solution results.
https://www.jise.ir/article_14559_1a641fb2bcd4fe26df91202d10247eb4.pdf
Disaster Management
Multi-Objective Optimization
routing
scheduling
eng
Iranian Institute of Industrial Engineering
Journal of Industrial and Systems Engineering
1735-8272
2717-3380
2016-07-01
9
3
28
56
14997
Demand-oriented timetable design for urban rail transit under stochastic demand
Erfan Hassannayebi
e.hassannayebi@modares.ac.ir
1
Seyed Hessameddin Zegordi
zegordi@modares.ac.ir
2
Mohammad Amin-Naseri
amin_nas@modares.ac.ir
3
Masoud Yaghini
yaghini@iust.ac.ir
4
Industrial Engineering Department, Tarbiat Modares University, Tehran, Iran.
Industrial Engineering Department, Tarbiat Modares University, Tehran, Iran
Industrial Engineering Department, Tarbiat Modares University, Tehran, Iran
School of Railway Engineering, Iran University of Science and Technology, Tehran, Iran
In the context of public transportation system, improving the service quality and robustness through minimizing the average passengers waiting time is a real challenge. This study provides robust stochastic programming models for train timetabling problem in urban rail transit systems. The objective is minimization of the weighted summation of the expected cost of passenger waiting time, its variance and the penalty function including the capacity violation due to overcrowding. In the proposed formulations, the dynamic and uncertain travel demand is represented by the scenario-based multi-period arrival rates of passenger. Two versions of the robust stochastic programming models are developed and a comparative analysis is conducted to testify the tractability of the models. The effectiveness of the proposed stochastic programming model was demonstrated through the application to Tehran underground urban railway. The outcomes show the reductions in expected passenger waiting time of 22%, and cost variance drop of 60% compared with the baseline plans using the proposed robust optimization approach.
https://www.jise.ir/article_14997_d21de2110385f43fcbf192ad70357850.pdf
Train timetabling
Urban rail
uncertain demand, robust stochastic programming
eng
Iranian Institute of Industrial Engineering
Journal of Industrial and Systems Engineering
1735-8272
2717-3380
2016-07-01
9
3
57
69
13968
A Hybrid Modified Meta-heuristic Algorithm for Solving the Traveling Salesman Problem
Hassan Zarei
zarei2003@gmail.com
1
Majid Yousefi Khoshbakht
khoshbakht@iauh.ac.ir
2
Esmaeel Khorram
eskhorr@aut.ac.ir
3
Department of Mathematics, Payame Noor University, Tehran, Iran
Young Researchers & Elites Club, Hamedan Branch, Islamic Azad University, Hamedan, Iran
Department of Mathematics and Computer Science, Amirkabir University of Technology
The traveling salesman problem (TSP) is one of the most important combinational optimization problems that have nowadays received much attention because of its practical applications in industrial and service problems. In this paper, a hybrid two-phase meta-heuristic algorithm called MACSGA used for solving the TSP is presented. At the first stage, the TSP is solved by the modified ant colony system (MACS) in each iteration, and at the second stage, the modified genetic algorithm (GA) and 2-opt local search are used for improving the solutions of the ants for that iteration. This process avoids the premature convergence and makes better solutions. Computational results on several standard instances of TSP show the efficiency of the proposed algorithm compared with the GA, ant colony optimization and other meta-heuristic algorithms.
https://www.jise.ir/article_13968_da70337d040a93df6acf54667bfa7d5c.pdf
Genetic algorithm
ant colony system
Traveling Salesman Problem
Premature Convergence
eng
Iranian Institute of Industrial Engineering
Journal of Industrial and Systems Engineering
1735-8272
2717-3380
2016-07-01
9
3
70
81
14999
A Multi-commodity Pickup and Delivery Open-tour m-TSP Formulation for Bike Sharing Rebalancing Problem
S. Mohammad Arabzad
m.arabzad@yahoo.com
1
Hadi Shirouyehzad
hadi.shirouyehzad@gmail.com
2
Mahdi Bashiri
bashiri@shahed.ac.ir
3
Reza moghaddam
tavakoli@ut.ac.ir
4
Esmaeil Najafi
najafi1515@yahoo.com
5
Department of Industrial Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran
Department of Industrial Engineering, Najafabad Branch, Islamic Azad University, Najafabad, Iran
Department of Industrial Engineering, Shahed University, Tehran, Iran
School of Industrial Engineering, College of Engineering, University of Tehran, Tehran, Iran
Department of Industrial Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran
Bike sharing systems (BSSs) offer a mobility service whereby public bikes, located at different stations across an urban area, are available for shared use. An important point is that the distribution of rides between stations is not uniformly distributed and certain stations fill up or empty over time. These empty and full stations lead to demand for bikes and return boxes that cannot be fulfilled leading to unsatisfied and possibly even lost customers. To avoid this situation, bikes in the systems are redistributed by the provider. In this paper, a mathematical modelling is proposed to rebalance the stations employing non-identical trucks based on Travelling Salesman Problem (TSP) formulation. This modelling is categorized as static repositioning where the demands of stations in one period is considered. In the modelling, several types of bikes have been considered in BSSs and it has assumed that there are two depots and trucks start from one and return to another one. Finally, a numerical example confirms the applicability of the proposed model. The result shows that the modelling would simultaneously obtain the minimum paths, the minimum implementing truck’s costs and the minimum of loading/unloading bikes program.
https://www.jise.ir/article_14999_f9b468d8aa2ca2931932fdc208347ad3.pdf
Bike Sharing Systems (BSSs)
rebalancing
Travelling Salesman Problem (TSP)
mathematical programming
eng
Iranian Institute of Industrial Engineering
Journal of Industrial and Systems Engineering
1735-8272
2717-3380
2016-07-01
9
3
82
95
15000
Using data envelopment analysis (DEA) to improve the sales performance in Iranian agricultural clusters by utilizing business networks and business development services providers (BDSPs)
Abdorrahman Haeri
ahaeri@iust.ac.ir
1
Rouzbeh Ghousi
ghousi@iust.ac.ir
2
School of Industrial Engineering, Iran University of Science & Technology, Tehran, Iran
School of Industrial Engineering, Iran University of Science & Technology, Tehran, Iran
Business clusters play an important role in developing and improving the economic performance of countries and in promoting the welfare of people. Business development service providers (hereafter referred to as, BDSP) have a considerable role in providing specialized services pertinent to the conditions of active enterprises in clusters and in promoting their performance level in order to improve their competitiveness compared to large enterprises. In this study, data envelopment analysis (DEA) was used with respect to three inputs (the number of active networks, active BDSPs, staff in the cluster) and two outputs (the amount of domestic sales and exports). DEA model has been used in order to provide an accurate and comprehensive analysis of the eight agricultural clusters under study while some of the above-mentioned inputs and outputs have been considered. The performance of clusters can be compared together from different aspects and perspectives. For example, domestic sales was considered as the output factor only once, and so was export and, then, the performance of agricultural clusters were compared with each other. It should be noted that the clusters under study are active in terms of the processing of agricultural products, such as gardening products, dates, saffron, tea, and pistachios.
https://www.jise.ir/article_15000_90513ab48ef1937da3829afd7e9e7d22.pdf
Data Envelopment Analysis
agricultural clusters
business development services providers
Agricultural products
efficiency evaluation
eng
Iranian Institute of Industrial Engineering
Journal of Industrial and Systems Engineering
1735-8272
2717-3380
2016-07-01
9
3
96
110
15108
Interval-Valued Hesitant Fuzzy Method based on Group Decision Analysis for Estimating Weights of Decision Makers
Hossein Gitinavard
h.gitinavard@gmail.com
1
Ahmad Makui
amakui@iust.ac.ir
2
Armin Jabbarzadeh
arminj@iust.ac.ir
3
School of Industrial Engineering, Iran University of Science and Technology, Tehran, Iran
School of Industrial Engineering, Iran University of Science and Technology, Tehran, Iran
School of Industrial Engineering, Iran University of Science and Technology, Tehran, Iran
In this paper, a new soft computing group decision method based on the concept of compromise ratio is introduced for determining decision makers (DMs)' weights through the group decision process under uncertainty. In this method, preferences and judgments of the DMs or experts are expressed by linguistic terms for rating the industrial alternatives among selected criteria as well as the relative significance of each criterion. The DMs’ opinions are demonstrated by a decision matrix in interval-valued hesitant fuzzy sets (IVHFSs). In addition, the interval-valued hesitant fuzzy positive and negative ideal solutions are defined by the matrix, respectively. Then, the hesitant fuzzy average and worst group scores of the DMs’ decision matrix from matrices of interval-valued hesitant fuzzy positive and negative ideal solutions are described based on n-dimensional interval-valued hesitant fuzzy Euclidean distance measure. Further, a novel collective index is introduced based on the IVHFS to determine the weight of each DM or expert in the group decision process. Finally, an application example in industrial selection problems is presented about the best site selection for building a new factory to explain the computation process of the proposed soft computing group decision method in detail.
https://www.jise.ir/article_15108_249cff7693e31163966140b4d0d0fd4c.pdf
Site location selection problem
Interval-valued hesitant fuzzy sets
Decision makers’ weights
multi-criteria group decision making
eng
Iranian Institute of Industrial Engineering
Journal of Industrial and Systems Engineering
1735-8272
2717-3380
2016-07-01
9
3
111
126
15309
Benders’ decomposition algorithm to solve bi-level bi-objective scheduling of aircrafts and gate assignment under uncertainty
Mohsen Amal Nik
amalnick@ut.ac.ir
1
Javad Ansarifar
javad.ansarifar@ut.ac.ir
2
Faezeh Akhavizadegan
f.akhavizadegan@ut.ac.ir
3
School of Industrial Engineering, College of Engineering, University of Tehran, Tehran, Iran
School of Industrial Engineering, College of Engineering, University of Tehran, Tehran, Iran
School of Industrial Engineering, College of Engineering, University of Tehran, Tehran, Iran
Management and scheduling of flights and assignment of gates to aircraft play a significant role to improve the performance of the airport, due to the growing number of flights and decreasing the flight times. This research addresses the assignement and scheduling problem of runways and gates simultaneously. Moreover, this research is the first study that considers the constraint of unavailability of runway’s and the uncertain parameters relating to both areas of runway and gate assignment. One of the distinguishing contributions of the proposed model is that the problem is formulated as a bi-level bi-objective one. The leader objective function minimizes the total waiting time for runways and gates for all aircrafts based on their importance coefficient. Meanwhile, the total distance traveled by all passengers in the airport terminal is minimized by a follower objective function. To solve the proposed model, Benders’ decomposition method is applied. Empirical data are used to show the validation and application of the proposed model. A comparison shows the effectiveness of the model and its significant impact on decreasing the costs.
https://www.jise.ir/article_15309_e5044ad6b903fdcc1a2deb4e7720d5d1.pdf
Aircraft scheduling
Gate Assignment
multi-objective
bi-level
fuzzy programming
Benders’ decomposition algorithm
eng
Iranian Institute of Industrial Engineering
Journal of Industrial and Systems Engineering
1735-8272
2717-3380
2016-07-01
9
3
127
145
16498
Economical-Statistical design of one- sided CCC-r control chart based on analytical hierarchy process
Mohammad Fallah Nezhad
fallahnezhad@yazd.ac.ir
1
Yousof Shamstabar
y.shamstabar@gmail.com
2
Yazd University
Yazd University
The cumulative count of a conforming (CCC) control chart is used for high quality processes.The CCC − r chart is an improvement of the CCC chart that is based on the cumulative number of items inspected until observing r non-conforming ones. This paper aims to propose a new approach for manufacturer’s decision making according to the criteria among the available options. The objective function of the proposed model is to minimize three criteria simultaneously, including expected cost per hour(C), modified producer risk (PR) and modified consumer risk (CR).the solution method for the proposed model is designed by using AHP technique and a case study is analyzed described in numerical illustration section. In addition, sensitivity analysis is performed to illustrate efficacy of the input parameters on the optimal solutions of the proposed model.
https://www.jise.ir/article_16498_b5219cb029ff922943133110fa6d73e6.pdf
Statistical process control
CCC-r charts
high quality processes
Multiple Attribute Decision Making (MADM)
AHP technique
eng
Iranian Institute of Industrial Engineering
Journal of Industrial and Systems Engineering
1735-8272
2717-3380
2016-07-01
9
3
146
164
16499
Improvement of project management office performance: An empirical investigation of effective factors in iranian construction industry
Mahmoud Ershadi
mahmood_ershadi@yahoo.com
1
Reza Atashfaraz
rezaatashfaraz1@yahoo.com
2
Industrial Engineering Dept., IHCU University, Tehran, Iran
Project and Construction Management, Shahid Beheshti University, Tehran, Iran.
Project management office (PMO) is a new emerging concept in Iranian construction industry. Executives expect this organizational unit to add value to the business, and meet the demands of stakeholders by performing specialized tasks ranging from providing project management support to portfolio management. In this regard, PMO managers have long faced the question of how to improve the performance of project management office. Regarding the lack of research on this subject, current study focuses on identifying and analyzing the factors positively affecting the project management office performance in Iranian construction industry. The theoretical basis was extracted from the literature, and a field research was conducted for examining factors in Iranian construction industry. The parametric t-test hypothesis testing was used to identify key factors, and the interpretive structural modeling was applied to provide an overview on their interrelationships. The final conceptual model of factors indicates 9 factors in 6 level grouped in 3 category (dependent, linkage and driver variables). Furthermore, the findings provide Iranian construction companies with common understanding, and practical guidelines to steer their project management offices toward creating higher value.
https://www.jise.ir/article_16499_40113509c6821fe780f88b8cbfded5cb.pdf
Project Management Office
Performance Management
Interpretive structural modeling
Iranian Construction Industry