Iranian Institute of Industrial Engineering
Journal of Industrial and Systems Engineering
1735-8272
2717-3380
9
3
2016
07
01
Truck scheduling problem in a cross-docking system with release time constraint
1
16
EN
Jamal
Arkat
Industrial Engineering Department, University of Kurdistan
j.arkat@uok.ac.ir
Parak
Qods
Department of Industrial Engineering, University of Kurdistan
parak.qods@gmail.com
Fardin
Ahmadizar
0000-0002-8615-9893
Sanandaj, University of Kurdistan, Department of Industrial Engineering
f.ahmadizar@uok.ac.ir
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.
cross-docking,Truck scheduling,Release time,Simulated Annealing Algorithm
https://www.jise.ir/article_14558.html
https://www.jise.ir/article_14558_314cd2b5606e6909af6179dd13f06cf3.pdf
Iranian Institute of Industrial Engineering
Journal of Industrial and Systems Engineering
1735-8272
2717-3380
9
3
2016
07
01
Multi-objective routing and scheduling for relief distribution with split delivery in post-disaster response
17
27
EN
Fatemeh
Sabouhi
School of Industrial Engineering, Iran University of Science & Technology, Tehran, Iran
s_fatemeh_3359@yahoo.com
Mehdi
Heydari
School of Industrial Engineering, Iran University of Science & Technology, Tehran, Iran
mheydari@iust.ac.ir
Ali
Bozorgi-Amiri
0000-0002-1180-9572
School of Industrial Engineering, College of Engineering, University of Tehran, Tehran, Iran
alibozorgi@ut.ac.ir
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.
Disaster Management,Multi-Objective Optimization,routing,scheduling
https://www.jise.ir/article_14559.html
https://www.jise.ir/article_14559_1a641fb2bcd4fe26df91202d10247eb4.pdf
Iranian Institute of Industrial Engineering
Journal of Industrial and Systems Engineering
1735-8272
2717-3380
9
3
2016
07
01
Demand-oriented timetable design for urban rail transit under stochastic demand
28
56
EN
Erfan
Hassannayebi
Industrial Engineering Department, Tarbiat Modares University, Tehran, Iran.
e.hassannayebi@modares.ac.ir
Seyed Hessameddin
Zegordi
Industrial Engineering Department, Tarbiat Modares University, Tehran, Iran
zegordi@modares.ac.ir
Mohammad
Reza
Amin-Naseri
Industrial Engineering Department, Tarbiat Modares University, Tehran, Iran
amin_nas@modares.ac.ir
Masoud
Yaghini
School of Railway Engineering, Iran University of Science and Technology, Tehran, Iran
yaghini@iust.ac.ir
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.
Train timetabling,Urban rail,uncertain demand, robust stochastic programming
https://www.jise.ir/article_14997.html
https://www.jise.ir/article_14997_d21de2110385f43fcbf192ad70357850.pdf
Iranian Institute of Industrial Engineering
Journal of Industrial and Systems Engineering
1735-8272
2717-3380
9
3
2016
07
01
A Hybrid Modified Meta-heuristic Algorithm for Solving the Traveling Salesman Problem
57
69
EN
Hassan
Zarei
Department of Mathematics, Payame Noor University, Tehran, Iran
zarei2003@gmail.com
Majid
Yousefi Khoshbakht
Young Researchers & Elites Club, Hamedan Branch, Islamic Azad University, Hamedan, Iran
khoshbakht@iauh.ac.ir
Esmaeel
Khorram
Department of Mathematics and Computer Science, Amirkabir University of Technology
eskhorr@aut.ac.ir
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.
Genetic algorithm,ant colony system,Traveling Salesman Problem,Premature Convergence
https://www.jise.ir/article_13968.html
https://www.jise.ir/article_13968_da70337d040a93df6acf54667bfa7d5c.pdf
Iranian Institute of Industrial Engineering
Journal of Industrial and Systems Engineering
1735-8272
2717-3380
9
3
2016
07
01
A Multi-commodity Pickup and Delivery Open-tour m-TSP Formulation for Bike Sharing Rebalancing Problem
70
81
EN
S. Mohammad
Arabzad
Department of Industrial Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran
m.arabzad@yahoo.com
Hadi
Shirouyehzad
Department of Industrial Engineering, Najafabad Branch, Islamic Azad University, Najafabad, Iran
hadi.shirouyehzad@gmail.com
Mahdi
Bashiri
Department of Industrial Engineering, Shahed University, Tehran, Iran
bashiri@shahed.ac.ir
Reza
Tavakkoli-
moghaddam
0000-0002-6757-926X
School of Industrial Engineering, College of Engineering, University of Tehran, Tehran, Iran
tavakoli@ut.ac.ir
Esmaeil
Najafi
Department of Industrial Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran
najafi1515@yahoo.com
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.<br /> <strong><em> </em></strong>
Bike Sharing Systems (BSSs),rebalancing,Travelling Salesman Problem (TSP),mathematical programming
https://www.jise.ir/article_14999.html
https://www.jise.ir/article_14999_f9b468d8aa2ca2931932fdc208347ad3.pdf
Iranian Institute of Industrial Engineering
Journal of Industrial and Systems Engineering
1735-8272
2717-3380
9
3
2016
07
01
Using data envelopment analysis (DEA) to improve the sales performance in Iranian agricultural clusters by utilizing business networks and business development services providers (BDSPs)
82
95
EN
Abdorrahman
Haeri
School of Industrial Engineering, Iran University of Science & Technology, Tehran, Iran
ahaeri@iust.ac.ir
Rouzbeh
Ghousi
0000-0002-5839-5792
School of Industrial Engineering, Iran University of Science & Technology, Tehran, Iran
ghousi@iust.ac.ir
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.
Data Envelopment Analysis,agricultural clusters,business development services providers,Agricultural products,efficiency evaluation
https://www.jise.ir/article_15000.html
https://www.jise.ir/article_15000_90513ab48ef1937da3829afd7e9e7d22.pdf
Iranian Institute of Industrial Engineering
Journal of Industrial and Systems Engineering
1735-8272
2717-3380
9
3
2016
07
01
Interval-Valued Hesitant Fuzzy Method based on Group Decision Analysis for Estimating Weights of Decision Makers
96
110
EN
Hossein
Gitinavard
School of Industrial Engineering, Iran University of Science and Technology, Tehran, Iran
h.gitinavard@gmail.com
Ahmad
Makui
0000-0001-6249-530X
School of Industrial Engineering, Iran University of Science and Technology, Tehran, Iran
amakui@iust.ac.ir
Armin
Jabbarzadeh
School of Industrial Engineering, Iran University of Science and Technology, Tehran, Iran
arminj@iust.ac.ir
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 <em>n</em>-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.
Site location selection problem,Interval-valued hesitant fuzzy sets,Decision makers’ weights,multi-criteria group decision making
https://www.jise.ir/article_15108.html
https://www.jise.ir/article_15108_249cff7693e31163966140b4d0d0fd4c.pdf
Iranian Institute of Industrial Engineering
Journal of Industrial and Systems Engineering
1735-8272
2717-3380
9
3
2016
07
01
Benders’ decomposition algorithm to solve bi-level bi-objective scheduling of aircrafts and gate assignment under uncertainty
111
126
EN
Mohsen
Sadegh
Amal Nik
School of Industrial Engineering, College of Engineering, University of Tehran, Tehran, Iran
amalnick@ut.ac.ir
Javad
Ansarifar
School of Industrial Engineering, College of Engineering, University of Tehran, Tehran, Iran
javad.ansarifar@ut.ac.ir
Faezeh
Akhavizadegan
School of Industrial Engineering, College of Engineering, University of Tehran, Tehran, Iran
f.akhavizadegan@ut.ac.ir
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.
Aircraft scheduling,Gate Assignment,multi-objective,bi-level,fuzzy programming,Benders’ decomposition algorithm
https://www.jise.ir/article_15309.html
https://www.jise.ir/article_15309_e5044ad6b903fdcc1a2deb4e7720d5d1.pdf
Iranian Institute of Industrial Engineering
Journal of Industrial and Systems Engineering
1735-8272
2717-3380
9
3
2016
07
01
Economical-Statistical design of one- sided CCC-r control chart based on analytical hierarchy process
127
145
EN
Mohammad
Saber
Fallah Nezhad
Yazd University
fallahnezhad@yazd.ac.ir
Yousof
Shamstabar
Yazd University
y.shamstabar@gmail.com
The cumulative count of a conforming (CCC) control chart is used for high quality processes.The CCC − <em>r </em>chart is an improvement of the CCC chart that is based on the cumulative number of items inspected until observing <em>r </em>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.
Statistical process control,CCC-r charts,high quality processes,Multiple Attribute Decision Making (MADM),AHP technique
https://www.jise.ir/article_16498.html
https://www.jise.ir/article_16498_b5219cb029ff922943133110fa6d73e6.pdf
Iranian Institute of Industrial Engineering
Journal of Industrial and Systems Engineering
1735-8272
2717-3380
9
3
2016
07
01
Improvement of project management office performance: An empirical investigation of effective factors in iranian construction industry
146
164
EN
Mahmoud
Ershadi
Industrial Engineering Dept., IHCU University, Tehran, Iran
mahmood_ershadi@yahoo.com
Reza
Atashfaraz
Project and Construction Management, Shahid Beheshti University, Tehran, Iran.
rezaatashfaraz1@yahoo.com
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.
Project Management Office,Performance Management,Interpretive structural modeling,Iranian Construction Industry
https://www.jise.ir/article_16499.html
https://www.jise.ir/article_16499_40113509c6821fe780f88b8cbfded5cb.pdf