Parviz Fattahi | Alzahra University (original) (raw)
Papers by Parviz Fattahi
In this paper, a new approach to overlapping operations in job shop scheduling is presented. In m... more In this paper, a new approach to overlapping operations in job shop scheduling is presented. In many job shops, a customer demand can be met in more than one way for each job, where demand determines the quantity of each finished job ordered by a customer. In each job, embedded operations can be performed due to overlapping considerations in which each operation may be overlapped with the others because of its nature. The effects of the new approach on job shop scheduling problems are evaluated. Since the problem is well known as NP-Hard class, a simulated annealing algorithm is developed to solve large scale problems. Moreover, a mixed integer linear programming (MILP) method is applied to validate the proposed algorithm. The approach is tested on a set of random data to evaluate and study the behavior of the proposed algorithm. Computational experiments confirmed superiority of the proposed approach. To evaluate the effect of overlapping considerations on the job shop scheduling p...
Job shop scheduling problem (JSP) is an attractive field for researchers and production managers ... more Job shop scheduling problem (JSP) is an attractive field for researchers and production managers since it is a famous problem in many industries and a complex problem for researchers. Due to NP-hardness property of this problem, many meta-heuristics are developed to solve it. Solution representation (solution seed) is an important element for any meta-heuristic algorithm. Therefore, many researchers try to present different encodings to solve this problem. Fattahi et al., and Gen & Cheng suggested two solutions for this problem that both have advantages and weaknesses in searching solution space to reach an acceptable solution. In the current paper, a cyclic algorithm based on tabu search algorithm was proposed to improve the exploration and exploitation powers of these encodings. Also, several problems of different sizes are solved by it and the obtained results were compared. Results showed the applicability and effectiveness of the proposed solution representation in comparison w...
هدیکچ قیقحت نیا رد هلاسم لقادح فده اب هلومحم نایرج و يزاوم ژاتنوم هلحرم کی اب هارمه یهاگراک دیلوت... more هدیکچ قیقحت نیا رد هلاسم لقادح فده اب هلومحم نایرج و يزاوم ژاتنوم هلحرم کی اب هارمه یهاگراک دیلوت يدنبنامز تسا هدش هتفرگ رظن رد تلاوصحم لیمکت نامز ندرک . هب ادتبا حیرشت روظنم هلاسم همانرب لدم کی ، یـطخ يزـیر طلتخم حیحص ددع هیارا دیدرگ . هـنومن دنچ لدم درکلمع تحص یسررب تهج سپس هلاـسم اـب کـچوک هزادـنا طسوت GAMS دش لح . هب هجوت اب NP-hard ندوب هلاسم رد نآ لح يارب متیروگلا زا گرزب و طسوتم داعبا ياـه هیبش و کیتنژ یبیکرت دیدرگ هدافتسا يزاوم ریغتم یگیاسمه يوجتسج و ریغتم یگیاسمه يوجتسج ،دیربت يزاس . مه نینچ نومزآ زا متیروگلا ییاناوت یسررب تهج اـمآ ياه هدافتـسا یبـسن فارـحنا دـصرد درـکلمع راـیعم و ير تبسن ار يزاوم ریغتم یگیاسمه يوجتسج و کیتنژ یبیکرت متیروگلا بسانم درکلمع یتابساحم جیاتن هک دیدرگ متیروگلا ریاس هب باوج بسک رد اه داد ناشن تیفیک اب ياه .
In this paper, a Job shop scheduling problem with a parallel assembly stage and Lot Streaming (LS... more In this paper, a Job shop scheduling problem with a parallel assembly stage and Lot Streaming (LS) is considered for the first time in both machining and assembly stages. Lot Streaming technique is a process of splitting jobs into smaller sub-jobs such that successive operations can be overlapped. Hence, to solve job shop scheduling problem with a parallel assembly stage and lot streaming, decision makers not only need to determine the processing sequences on machines in first stage, but also need to assign each product to a machine and determine the assembly sequences of the products in second stage and the sub-lot sizes of all jobs and products to minimize the makespan. At first, this problem is modeled as a mixed integer linear programming and GAMS software is applied to solve small problems. Since this problem is classified as NP-hard, four hybrid algorithms based on iterative procedures are suggested to solve the problem in medium and large dimensions. In order to verify the ef...
PurposeThe purpose of this paper is to present an integrated strategy for inventory control and p... more PurposeThe purpose of this paper is to present an integrated strategy for inventory control and preventive maintenance planning for a single-machine production system with increasing failure rates.Design/methodology/approachThere are three scenarios for solving presented model. The strategy is such that the production component is placed under maintenance as soon as it reaches the m level or in the event of a malfunction earlier than m. Maintenance completion time is not predictable. As a result of periodic maintenance, a buffer stock h is held and the production component starts to produce from period A with the maximum throughput to satisfy demand and handle the shortage. A numerical algorithm to find the optimal policy is developed. The algorithm is implemented using MATLAB software.FindingsThe authors discovered that joint optimization mainly reduces production system costs. Cs is holding cost of a product unit during a unit of time. The authors consider two values for Cs, consi...
One of the most important problems in managing the final assembly line of the car manufacturing f... more One of the most important problems in managing the final assembly line of the car manufacturing factories is Car Sequencing Problem (CSP). By solving this problem, the optimal permutation of car models is determined in a mixed model assembly line (MMAL). In a realistic circumstance, unforeseen occurrence of disturbances like shortage or delay in feeding required parts to the assembly line, cause to stir up an initially planned sequence. In this situation, another challenging problem should be solved that is car resequencing. This study treats the car resequencing problem where there is an intermediate buffer before final assembly line to rearrange a given initial sequence. Two objective functions are considered: (1) minimizing the ratio constraint violations (classic objective of car sequencing problem), and (2) minimizing work in process that remained in painted body storage (PBS) buffer. For this problem, a mixed integer linear programming (MIP) mathematical model is developed. Si...
In this paper, an analytical approach is used for assembly line rebalancing and worker assignment... more In this paper, an analytical approach is used for assembly line rebalancing and worker assignment for single and mixed-model assembly lines based on a heuristic-simulation algorithm. This approach helps to managers to select a better marketing strategy when different combinations of demands are suitable.Furthermore, they can use it as a guideline to know which worker assignment is better for each combination. We show the efficiency of the proposed approach for single and mixed-model assembly lines using different benchmarked standard test problems with different number of tasks, stations, skilled workers and demands. Comparisons show the heuristic-simulation algorithm is faster than the GAMS software, and its results are optimum or very close to the optimum values.
Journal of Modelling in Management
Purpose This study aims to design a supply chain network in an uncertain environment while exists... more Purpose This study aims to design a supply chain network in an uncertain environment while exists two options for distribution of the perishable product and production lot-sizing is concerned. Design/methodology/approach Owing to the complexity of the mathematical model, a solution approach based on a Lagrangian relaxation (LR) heuristic is developed which provides good-quality upper and lower bounds. Findings The model output is discussed through various examples. The introduction of some enhancements and using some heuristics results in better outputs in the solution procedure. Practical implications This paper covers the modeling of some real-world problems in which demand is uncertain and managers face making some concurrent decisions related to supply chain management, transportation and logistics and inventory control issues. Furthermore, considering the perishability of product in modeling makes the problem more practically significant as these days there are many supply chai...
Assembly Automation
Purpose The purpose of this paper is to present a mathematical model and a new hybrid algorithm f... more Purpose The purpose of this paper is to present a mathematical model and a new hybrid algorithm for flexible job shop scheduling problem with assembly operations. In this problem, each product is produced by assembling a set of several different parts. At first, the parts are processed in a flexible job shop system, and then at the second stage, the parts are assembled and products are produced. Design/methodology/approach As the problem is non-deterministic polynomial-time-hard, a new hybrid particle swarm optimization and parallel variable neighborhood search (HPSOPVNS) algorithm is proposed. In this hybrid algorithm, particle swarm optimization (PSO) algorithm is used for global exploration of search space and parallel variable neighborhood search (PVNS) algorithm for local search at vicinity of solutions obtained in each iteration. For parameter tuning of the metaheuristic algorithms, Taguchi approach is used. Also, a statistical test is proposed to compare the ability of metahe...
International Journal of Engineering
In this paper, a flowshop scheduling problem is studied. The importance of this study is that it ... more In this paper, a flowshop scheduling problem is studied. The importance of this study is that it considers different constraints simultaneously. These constraints are Lot Streaming, Position based learning factors, sequence dependent setup times and the fact that the flowshop line is no-wait. Lot streaming divide the lots of products into portions called sublots in order to reduce the lead times and work-in-process, and increase the machine utilization rates. The objective is to minimize the makespan. To clarify the system, mathematical model of the problemis presented. Since the problemis strongly NP-hard, two hybrid metaheuristics algorithms are proposed to solve the problem. These algorithms are based on the Variable Neighborhood Search (VNS), which is proved as an effective method for combinatorial optimization problems. In the proposed VNS, an efficient scheme for neighborhood search based on Tabu Search (TS) and Simulated Annealing (SA) is presented to strengthen the local searches. At the last part, computation results are provided to evaluate the efficiency of VNSSA and VNSTS. In order to verify the effectiveness of proposed algorithms, Relative percentage Deviation along with statistical analysis is presented.The computational results show that VNSSA outperforms VNSTS in most instances.
Operational Research
Multi-product pipelines are a significant and extensive mean of transporting petroleum based prod... more Multi-product pipelines are a significant and extensive mean of transporting petroleum based products from refineries to distribution centers. Previous contributions on tree-like pipeline scheduling problem have considered a simple structure with a single refinery connected to a mainline and some secondary lines only emerged from the mainline. In practice, however, a tree-like pipeline may also have several branches on a secondary line resulting in a complex structure, the so called multi-level tree-like pipeline. This paper addresses the short-term scheduling of multi-level tree-like pipelines with multiple refineries through a continuous time mixed-integer linear programming (MILP) model that considers multiple intermediate due dates for product demands. The objective is to satisfy product demands on time at the minimum operational costs, such as pumping, interface and backorder costs. The proposed model performance’s is shown by solving four examples.
International Journal of Engineering
This paper addresses a multi-objective mathematical model for the mixed-model two-sided assembly ... more This paper addresses a multi-objective mathematical model for the mixed-model two-sided assembly line balancing and worker assignment with different skills. In this problem, the operation time of each task is dependent on the skill of the worker. The following objective functions are considered in the mathematical model: (1) minimizing the number of mated-stations, (2) minimizing the number of stations, and (3) minimizing the total human cost for a given cycle time. Furthermore, maximizing the weighted line efficiency and minimizing the weighted smoothness are two indices considered simultaneously in this paper. Since this problem is well-known as NP-hard class, a particle swarm optimization (PSO) algorithm is developed to solve it. The performance of the proposed PSO algorithm is evaluated with a simulated annealing (SA) algorithm existing in the literature over several benchmarked test problems for the conditions of the current problem in terms of running time and solution quality. The results show the proposed algorithm is an efficient algorithm.
International Journal of Production Research
ABSTRACT In this paper, a three-stage assembly flow shop scheduling problem with machine availabi... more ABSTRACT In this paper, a three-stage assembly flow shop scheduling problem with machine availability constraints is taken into account. Two objectives of minimising total weighted completion times (flow time) and minimising sum of weighted tardiness and earliness are simultaneously considered. To describe this problem, a mathematical model is presented. The problem is generalisation of three-machine flow shop scheduling problem and two-stage assembly flow shop scheduling problem. Since these problems are known to be NP-hard, the considered problem is also strongly NP-hard. Therefore, two multi-objective meta-heuristics are presented to efficiently solve this problem in a reasonable amount of time. Comprehensive computational experiments are performed to illustrate the performance of the presented algorithms.
Applied Mathematical Modelling, 2016
Facility location-allocation problems arise in many practical settings from emergency services to... more Facility location-allocation problems arise in many practical settings from emergency services to telecommunication networks. We propose a multi-objective multi-layer facility location-allocation (MLFLA) model with congested facilities using classical queuing systems. The goal is to determine the optimal number of facilities and the service allocation at each layer. We consider three objective functions aiming at: (1) minimizing the sum of aggregate travel and waiting times; (2) minimizing the cost of establishing the facilities; and (3) minimizing the maximum idle probability of the facilities. The problem is formulated as a multi-objective non-linear integer mathematical programming model. To find and analyze the Pareto optimal solutions, we propose a Pareto-based multi-objective metaheuristic approach based on the multi-objective vibration damping optimization (MOVDO) and the multi-objective harmony search algorithm (MOHSA). We demonstrate the effectiveness of the proposed model and exhibit the efficacy of the procedures and algorithms by comparing MOVDO and MOHSA with two well-known evolutionary algorithms, namely, the non-dominated sorting genetic algorithm (NSGA-II) and multi-objective simulated annealing (MOSA).
Computers & Operations Research, 2016
This paper presents a bi-objective mathematical programming model for the restricted facility loc... more This paper presents a bi-objective mathematical programming model for the restricted facility location problem, under a congestion and pricing policy. Motivated by various applications such as locating server on internet mirror sites and communication networks, this research investigates congested systems with immobile servers and stochastic demand as M/M/m/k queues. For this problem, we consider two simultaneous perspectives; (1) customers who desire to limit waiting time for service and (2) service providers who intend to increase profits. We formulate a bi-objective facility location problem with two objective functions: (i) maximizing total profit of the whole system and (ii) minimizing the sum of waiting time in queues; the model type is mixed-integer nonlinear. Then, a multi-objective optimization algorithm based on vibration theory (so-called multi-objective vibration damping optimization (MOVDO)), is developed to solve the model. Moreover, the Taguchi method is also implemented, using a response metric to tune the parameters. The results are analyzed and compared with a non-dominated sorting genetic algorithm (NSGA-II) as a well-developed multi-objective evolutionary optimization algorithm. Computational results demonstrate the efficiency of the proposed MOVDO to solve large-scale problems.
نشریه بین المللی مهندسی صنایع و مدیریت تولید, Nov 1, 2011
Greedy randomize adaptive search procedure is one of the repetitive meta-heuristic to solve combi... more Greedy randomize adaptive search procedure is one of the repetitive meta-heuristic to solve combinatorial problem. In this procedure, each repetition includes two, construction and local search phase. A high quality feasible primitive answer is made in construction phase and is improved in the second phase with local search. The best answer result of iterations, declare as output. In this study, GRASP is used to solve the QAP problem. The resulting on QAP library standard problem is used to demonstrate the high performance of suggested algorithm.
International Journal of Computer Integrated Manufacturing, Feb 6, 2014
ABSTRACT This article considers a particular case of the capacitated job shop scheduling problem ... more ABSTRACT This article considers a particular case of the capacitated job shop scheduling problem (CJSP) regarding sequence-dependent setup cost. At first, to formulate this problem a new mixed-integer programming (MIP) model is presented that minimises the sum of tardiness cost, overtime cost and setup cost. Then, due to the complexity of this problem, two novel hybrid approaches are developed to solve medium and large size problems. These proposed approaches are made based on two different combinations of tabu search and firefly algorithms: (i) integrated and (ii) hierarchical combination. Also, to improve the quality of solutions, in each step of the hybrid algorithms, an effective heuristic is proposed. This heuristic reduces the overtime costs of operations by efficient use of the operation’s slack. Moreover, to obtain better and more robust solutions, the Taguchi method is used to calibrate the parameters of the hybrid algorithms. Finally, the computational results are provided for evaluating the performance and effectiveness of the proposed solution approaches.
International Journal of Industrial Engineering Production Management, May 1, 2013
In this article, we integrate production and maintenance to two stage lot sizing models with a ce... more In this article, we integrate production and maintenance to two stage lot sizing models with a central warehouse and a manufacturer by adding a new constraint in which the demand is depend on the average percent of product shortage. The central warehouse faces stochastic demand and is controlled by continuous review (R,Q) policy. Additionally, Warehouse ordering cost can be reduced through further investment. In manufacturer system, assembly line needs two types of raw materials before converting them in to the finished product. One of them requires preprocessing inside the facility before the assembly operation and the other comes directly from outside supplier in assembly line. To analyze, we formulate a nonlinear cost function to aggregate all the costs. For doing this, we use Branch and Bound and nonlinear optimization technique-Generalized Reduced Gradient methods and compare the optimal value of these methods. The model is illustrated through numerical examples and sensitivity analyses on cost functions are presented.
In this paper, a new approach to overlapping operations in job shop scheduling is presented. In m... more In this paper, a new approach to overlapping operations in job shop scheduling is presented. In many job shops, a customer demand can be met in more than one way for each job, where demand determines the quantity of each finished job ordered by a customer. In each job, embedded operations can be performed due to overlapping considerations in which each operation may be overlapped with the others because of its nature. The effects of the new approach on job shop scheduling problems are evaluated. Since the problem is well known as NP-Hard class, a simulated annealing algorithm is developed to solve large scale problems. Moreover, a mixed integer linear programming (MILP) method is applied to validate the proposed algorithm. The approach is tested on a set of random data to evaluate and study the behavior of the proposed algorithm. Computational experiments confirmed superiority of the proposed approach. To evaluate the effect of overlapping considerations on the job shop scheduling p...
Job shop scheduling problem (JSP) is an attractive field for researchers and production managers ... more Job shop scheduling problem (JSP) is an attractive field for researchers and production managers since it is a famous problem in many industries and a complex problem for researchers. Due to NP-hardness property of this problem, many meta-heuristics are developed to solve it. Solution representation (solution seed) is an important element for any meta-heuristic algorithm. Therefore, many researchers try to present different encodings to solve this problem. Fattahi et al., and Gen & Cheng suggested two solutions for this problem that both have advantages and weaknesses in searching solution space to reach an acceptable solution. In the current paper, a cyclic algorithm based on tabu search algorithm was proposed to improve the exploration and exploitation powers of these encodings. Also, several problems of different sizes are solved by it and the obtained results were compared. Results showed the applicability and effectiveness of the proposed solution representation in comparison w...
هدیکچ قیقحت نیا رد هلاسم لقادح فده اب هلومحم نایرج و يزاوم ژاتنوم هلحرم کی اب هارمه یهاگراک دیلوت... more هدیکچ قیقحت نیا رد هلاسم لقادح فده اب هلومحم نایرج و يزاوم ژاتنوم هلحرم کی اب هارمه یهاگراک دیلوت يدنبنامز تسا هدش هتفرگ رظن رد تلاوصحم لیمکت نامز ندرک . هب ادتبا حیرشت روظنم هلاسم همانرب لدم کی ، یـطخ يزـیر طلتخم حیحص ددع هیارا دیدرگ . هـنومن دنچ لدم درکلمع تحص یسررب تهج سپس هلاـسم اـب کـچوک هزادـنا طسوت GAMS دش لح . هب هجوت اب NP-hard ندوب هلاسم رد نآ لح يارب متیروگلا زا گرزب و طسوتم داعبا ياـه هیبش و کیتنژ یبیکرت دیدرگ هدافتسا يزاوم ریغتم یگیاسمه يوجتسج و ریغتم یگیاسمه يوجتسج ،دیربت يزاس . مه نینچ نومزآ زا متیروگلا ییاناوت یسررب تهج اـمآ ياه هدافتـسا یبـسن فارـحنا دـصرد درـکلمع راـیعم و ير تبسن ار يزاوم ریغتم یگیاسمه يوجتسج و کیتنژ یبیکرت متیروگلا بسانم درکلمع یتابساحم جیاتن هک دیدرگ متیروگلا ریاس هب باوج بسک رد اه داد ناشن تیفیک اب ياه .
In this paper, a Job shop scheduling problem with a parallel assembly stage and Lot Streaming (LS... more In this paper, a Job shop scheduling problem with a parallel assembly stage and Lot Streaming (LS) is considered for the first time in both machining and assembly stages. Lot Streaming technique is a process of splitting jobs into smaller sub-jobs such that successive operations can be overlapped. Hence, to solve job shop scheduling problem with a parallel assembly stage and lot streaming, decision makers not only need to determine the processing sequences on machines in first stage, but also need to assign each product to a machine and determine the assembly sequences of the products in second stage and the sub-lot sizes of all jobs and products to minimize the makespan. At first, this problem is modeled as a mixed integer linear programming and GAMS software is applied to solve small problems. Since this problem is classified as NP-hard, four hybrid algorithms based on iterative procedures are suggested to solve the problem in medium and large dimensions. In order to verify the ef...
PurposeThe purpose of this paper is to present an integrated strategy for inventory control and p... more PurposeThe purpose of this paper is to present an integrated strategy for inventory control and preventive maintenance planning for a single-machine production system with increasing failure rates.Design/methodology/approachThere are three scenarios for solving presented model. The strategy is such that the production component is placed under maintenance as soon as it reaches the m level or in the event of a malfunction earlier than m. Maintenance completion time is not predictable. As a result of periodic maintenance, a buffer stock h is held and the production component starts to produce from period A with the maximum throughput to satisfy demand and handle the shortage. A numerical algorithm to find the optimal policy is developed. The algorithm is implemented using MATLAB software.FindingsThe authors discovered that joint optimization mainly reduces production system costs. Cs is holding cost of a product unit during a unit of time. The authors consider two values for Cs, consi...
One of the most important problems in managing the final assembly line of the car manufacturing f... more One of the most important problems in managing the final assembly line of the car manufacturing factories is Car Sequencing Problem (CSP). By solving this problem, the optimal permutation of car models is determined in a mixed model assembly line (MMAL). In a realistic circumstance, unforeseen occurrence of disturbances like shortage or delay in feeding required parts to the assembly line, cause to stir up an initially planned sequence. In this situation, another challenging problem should be solved that is car resequencing. This study treats the car resequencing problem where there is an intermediate buffer before final assembly line to rearrange a given initial sequence. Two objective functions are considered: (1) minimizing the ratio constraint violations (classic objective of car sequencing problem), and (2) minimizing work in process that remained in painted body storage (PBS) buffer. For this problem, a mixed integer linear programming (MIP) mathematical model is developed. Si...
In this paper, an analytical approach is used for assembly line rebalancing and worker assignment... more In this paper, an analytical approach is used for assembly line rebalancing and worker assignment for single and mixed-model assembly lines based on a heuristic-simulation algorithm. This approach helps to managers to select a better marketing strategy when different combinations of demands are suitable.Furthermore, they can use it as a guideline to know which worker assignment is better for each combination. We show the efficiency of the proposed approach for single and mixed-model assembly lines using different benchmarked standard test problems with different number of tasks, stations, skilled workers and demands. Comparisons show the heuristic-simulation algorithm is faster than the GAMS software, and its results are optimum or very close to the optimum values.
Journal of Modelling in Management
Purpose This study aims to design a supply chain network in an uncertain environment while exists... more Purpose This study aims to design a supply chain network in an uncertain environment while exists two options for distribution of the perishable product and production lot-sizing is concerned. Design/methodology/approach Owing to the complexity of the mathematical model, a solution approach based on a Lagrangian relaxation (LR) heuristic is developed which provides good-quality upper and lower bounds. Findings The model output is discussed through various examples. The introduction of some enhancements and using some heuristics results in better outputs in the solution procedure. Practical implications This paper covers the modeling of some real-world problems in which demand is uncertain and managers face making some concurrent decisions related to supply chain management, transportation and logistics and inventory control issues. Furthermore, considering the perishability of product in modeling makes the problem more practically significant as these days there are many supply chai...
Assembly Automation
Purpose The purpose of this paper is to present a mathematical model and a new hybrid algorithm f... more Purpose The purpose of this paper is to present a mathematical model and a new hybrid algorithm for flexible job shop scheduling problem with assembly operations. In this problem, each product is produced by assembling a set of several different parts. At first, the parts are processed in a flexible job shop system, and then at the second stage, the parts are assembled and products are produced. Design/methodology/approach As the problem is non-deterministic polynomial-time-hard, a new hybrid particle swarm optimization and parallel variable neighborhood search (HPSOPVNS) algorithm is proposed. In this hybrid algorithm, particle swarm optimization (PSO) algorithm is used for global exploration of search space and parallel variable neighborhood search (PVNS) algorithm for local search at vicinity of solutions obtained in each iteration. For parameter tuning of the metaheuristic algorithms, Taguchi approach is used. Also, a statistical test is proposed to compare the ability of metahe...
International Journal of Engineering
In this paper, a flowshop scheduling problem is studied. The importance of this study is that it ... more In this paper, a flowshop scheduling problem is studied. The importance of this study is that it considers different constraints simultaneously. These constraints are Lot Streaming, Position based learning factors, sequence dependent setup times and the fact that the flowshop line is no-wait. Lot streaming divide the lots of products into portions called sublots in order to reduce the lead times and work-in-process, and increase the machine utilization rates. The objective is to minimize the makespan. To clarify the system, mathematical model of the problemis presented. Since the problemis strongly NP-hard, two hybrid metaheuristics algorithms are proposed to solve the problem. These algorithms are based on the Variable Neighborhood Search (VNS), which is proved as an effective method for combinatorial optimization problems. In the proposed VNS, an efficient scheme for neighborhood search based on Tabu Search (TS) and Simulated Annealing (SA) is presented to strengthen the local searches. At the last part, computation results are provided to evaluate the efficiency of VNSSA and VNSTS. In order to verify the effectiveness of proposed algorithms, Relative percentage Deviation along with statistical analysis is presented.The computational results show that VNSSA outperforms VNSTS in most instances.
Operational Research
Multi-product pipelines are a significant and extensive mean of transporting petroleum based prod... more Multi-product pipelines are a significant and extensive mean of transporting petroleum based products from refineries to distribution centers. Previous contributions on tree-like pipeline scheduling problem have considered a simple structure with a single refinery connected to a mainline and some secondary lines only emerged from the mainline. In practice, however, a tree-like pipeline may also have several branches on a secondary line resulting in a complex structure, the so called multi-level tree-like pipeline. This paper addresses the short-term scheduling of multi-level tree-like pipelines with multiple refineries through a continuous time mixed-integer linear programming (MILP) model that considers multiple intermediate due dates for product demands. The objective is to satisfy product demands on time at the minimum operational costs, such as pumping, interface and backorder costs. The proposed model performance’s is shown by solving four examples.
International Journal of Engineering
This paper addresses a multi-objective mathematical model for the mixed-model two-sided assembly ... more This paper addresses a multi-objective mathematical model for the mixed-model two-sided assembly line balancing and worker assignment with different skills. In this problem, the operation time of each task is dependent on the skill of the worker. The following objective functions are considered in the mathematical model: (1) minimizing the number of mated-stations, (2) minimizing the number of stations, and (3) minimizing the total human cost for a given cycle time. Furthermore, maximizing the weighted line efficiency and minimizing the weighted smoothness are two indices considered simultaneously in this paper. Since this problem is well-known as NP-hard class, a particle swarm optimization (PSO) algorithm is developed to solve it. The performance of the proposed PSO algorithm is evaluated with a simulated annealing (SA) algorithm existing in the literature over several benchmarked test problems for the conditions of the current problem in terms of running time and solution quality. The results show the proposed algorithm is an efficient algorithm.
International Journal of Production Research
ABSTRACT In this paper, a three-stage assembly flow shop scheduling problem with machine availabi... more ABSTRACT In this paper, a three-stage assembly flow shop scheduling problem with machine availability constraints is taken into account. Two objectives of minimising total weighted completion times (flow time) and minimising sum of weighted tardiness and earliness are simultaneously considered. To describe this problem, a mathematical model is presented. The problem is generalisation of three-machine flow shop scheduling problem and two-stage assembly flow shop scheduling problem. Since these problems are known to be NP-hard, the considered problem is also strongly NP-hard. Therefore, two multi-objective meta-heuristics are presented to efficiently solve this problem in a reasonable amount of time. Comprehensive computational experiments are performed to illustrate the performance of the presented algorithms.
Applied Mathematical Modelling, 2016
Facility location-allocation problems arise in many practical settings from emergency services to... more Facility location-allocation problems arise in many practical settings from emergency services to telecommunication networks. We propose a multi-objective multi-layer facility location-allocation (MLFLA) model with congested facilities using classical queuing systems. The goal is to determine the optimal number of facilities and the service allocation at each layer. We consider three objective functions aiming at: (1) minimizing the sum of aggregate travel and waiting times; (2) minimizing the cost of establishing the facilities; and (3) minimizing the maximum idle probability of the facilities. The problem is formulated as a multi-objective non-linear integer mathematical programming model. To find and analyze the Pareto optimal solutions, we propose a Pareto-based multi-objective metaheuristic approach based on the multi-objective vibration damping optimization (MOVDO) and the multi-objective harmony search algorithm (MOHSA). We demonstrate the effectiveness of the proposed model and exhibit the efficacy of the procedures and algorithms by comparing MOVDO and MOHSA with two well-known evolutionary algorithms, namely, the non-dominated sorting genetic algorithm (NSGA-II) and multi-objective simulated annealing (MOSA).
Computers & Operations Research, 2016
This paper presents a bi-objective mathematical programming model for the restricted facility loc... more This paper presents a bi-objective mathematical programming model for the restricted facility location problem, under a congestion and pricing policy. Motivated by various applications such as locating server on internet mirror sites and communication networks, this research investigates congested systems with immobile servers and stochastic demand as M/M/m/k queues. For this problem, we consider two simultaneous perspectives; (1) customers who desire to limit waiting time for service and (2) service providers who intend to increase profits. We formulate a bi-objective facility location problem with two objective functions: (i) maximizing total profit of the whole system and (ii) minimizing the sum of waiting time in queues; the model type is mixed-integer nonlinear. Then, a multi-objective optimization algorithm based on vibration theory (so-called multi-objective vibration damping optimization (MOVDO)), is developed to solve the model. Moreover, the Taguchi method is also implemented, using a response metric to tune the parameters. The results are analyzed and compared with a non-dominated sorting genetic algorithm (NSGA-II) as a well-developed multi-objective evolutionary optimization algorithm. Computational results demonstrate the efficiency of the proposed MOVDO to solve large-scale problems.
نشریه بین المللی مهندسی صنایع و مدیریت تولید, Nov 1, 2011
Greedy randomize adaptive search procedure is one of the repetitive meta-heuristic to solve combi... more Greedy randomize adaptive search procedure is one of the repetitive meta-heuristic to solve combinatorial problem. In this procedure, each repetition includes two, construction and local search phase. A high quality feasible primitive answer is made in construction phase and is improved in the second phase with local search. The best answer result of iterations, declare as output. In this study, GRASP is used to solve the QAP problem. The resulting on QAP library standard problem is used to demonstrate the high performance of suggested algorithm.
International Journal of Computer Integrated Manufacturing, Feb 6, 2014
ABSTRACT This article considers a particular case of the capacitated job shop scheduling problem ... more ABSTRACT This article considers a particular case of the capacitated job shop scheduling problem (CJSP) regarding sequence-dependent setup cost. At first, to formulate this problem a new mixed-integer programming (MIP) model is presented that minimises the sum of tardiness cost, overtime cost and setup cost. Then, due to the complexity of this problem, two novel hybrid approaches are developed to solve medium and large size problems. These proposed approaches are made based on two different combinations of tabu search and firefly algorithms: (i) integrated and (ii) hierarchical combination. Also, to improve the quality of solutions, in each step of the hybrid algorithms, an effective heuristic is proposed. This heuristic reduces the overtime costs of operations by efficient use of the operation’s slack. Moreover, to obtain better and more robust solutions, the Taguchi method is used to calibrate the parameters of the hybrid algorithms. Finally, the computational results are provided for evaluating the performance and effectiveness of the proposed solution approaches.
International Journal of Industrial Engineering Production Management, May 1, 2013
In this article, we integrate production and maintenance to two stage lot sizing models with a ce... more In this article, we integrate production and maintenance to two stage lot sizing models with a central warehouse and a manufacturer by adding a new constraint in which the demand is depend on the average percent of product shortage. The central warehouse faces stochastic demand and is controlled by continuous review (R,Q) policy. Additionally, Warehouse ordering cost can be reduced through further investment. In manufacturer system, assembly line needs two types of raw materials before converting them in to the finished product. One of them requires preprocessing inside the facility before the assembly operation and the other comes directly from outside supplier in assembly line. To analyze, we formulate a nonlinear cost function to aggregate all the costs. For doing this, we use Branch and Bound and nonlinear optimization technique-Generalized Reduced Gradient methods and compare the optimal value of these methods. The model is illustrated through numerical examples and sensitivity analyses on cost functions are presented.