Scheduling
Esmaeil Mehdizadeh; Fatemeh Soleimaninia
Abstract
The Flexible Job shop Scheduling Problem (FJSP), as a Production Scheduling Problem (PSP), is generally an extension of the Job shop Scheduling Problem (JSP). In this paper, the FJSP with reverse flow consisting of two flows of jobs (direct and reverse) at each stage is studied; the first flow initiates ...
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The Flexible Job shop Scheduling Problem (FJSP), as a Production Scheduling Problem (PSP), is generally an extension of the Job shop Scheduling Problem (JSP). In this paper, the FJSP with reverse flow consisting of two flows of jobs (direct and reverse) at each stage is studied; the first flow initiates in Stage 1 and goes to Stage C (the last stage), and the second flow starts with Stage c and ends up in Stage 1. The aim is to minimize the makespan of the jobs (the maximum completion time). A Mixed Integer Programming (MIP) is presented to model the problem and the Branch and Bound (B&B) method is used to solve the problem. A numerical small-size problem is presented to demonstrate the applicability, for which the Lingo16 software is employed for a solution. Due to the NP-hardness of the problem, a meta-heuristic, namely the Vibration Damping Optimization (VDO) algorithm with tuned parameters using the Taguchi method, is utilized to solve large-scale problems. To validate the results obtained using the proposed solution algorithm in terms of the solution quality and the required computational time, they are compared with those obtained by the Lingo 16 software for small-size problems. Finally, the performance of the proposed algorithm is compared with a Genetic Algorithm (GA) by solving some randomly generated larger-size test problems, based on which the results are analyzed statistically. Computational results confirm the efficiency and effectiveness of the proposed algorithm and show that the VDO algorithm performs well.
Operations Research
Md. Kawsar Ahmed Asif; Shahriar Tanvir Alam; Sohana Jahan; Md. Rajib Arefin
Abstract
Sequencing and scheduling are the forms of decision-making approach that play a vital role in the automation and services industries. Efficient scheduling can help the industries to achieve the full potential of their supply chains. Conversely, inefficient scheduling causes additional idle time for machines ...
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Sequencing and scheduling are the forms of decision-making approach that play a vital role in the automation and services industries. Efficient scheduling can help the industries to achieve the full potential of their supply chains. Conversely, inefficient scheduling causes additional idle time for machines and reduces productivity, which may escalate the product price. This study aims to find the most effective algorithm for solving sequencing and scheduling problems in a non-preemptive flow shop environment where the objective functions are to reduce the total elapsed time and idle time. In this research, four prominent exact algorithms are considered and examined their efficiency by calculating the ‘total completion time’ and their goodness. In order to demonstrate the comparative analysis, numerical examples are illustrated. A Gantt chart is additionally conducted to exhibit the efficiency of these algorithms graphically. Eventually, a feasible outcome for each condition has been obtained by analyzing these four algorithms, which leads to getting a competent, time and cost-efficient algorithm.
Scheduling
N. MD. Sarfaraj; Md. L. R. Lingkon; N. Zahan
Abstract
The continuous growth of the population causes an increased demand for our healthcare services. Insufficient hospitals face challenges to serve the patient within a preferable duration. Long lines in front of counters increase the processing time of a patient. From the entry to the completion, plenty ...
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The continuous growth of the population causes an increased demand for our healthcare services. Insufficient hospitals face challenges to serve the patient within a preferable duration. Long lines in front of counters increase the processing time of a patient. From the entry to the completion, plenty of time waste just for unscheduled hospital management system. Job shop scheduling is an optimization process in which jobs are assigned with maintain a particular sequence. In this paper, we proposed flexible job shop scheduling to solve this type of problem by considering patients as job and test counter as machine for the optimization of the processing time and increase the efficiency of a hospital or a clinic. Genetic Algorithm was used to analyze the processing time for multiple counter of a hospital for a stable and effective scheduling. The results showed that an optimized makespan was generated and patients could fulfill their needs much quickly after applying flexible job shop scheduling.
Systems and service modeling and simulation
H. Amin-Tahmasbi; M. Hami
Abstract
In today’s competitive business environment, supply chain performance is one of the most critical issues in the various industries; there is much argumentation about the fact that supply chain performance is the basis of the supply chain management efficiency. In this regard, the distribution sector ...
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In today’s competitive business environment, supply chain performance is one of the most critical issues in the various industries; there is much argumentation about the fact that supply chain performance is the basis of the supply chain management efficiency. In this regard, the distribution sector is the most important part of the supply chain. Due to the pulse of a company is in the hands of its sales and distribution department. This article proposes a new mixed integrated linear programming model MILP for scheduling distribution channel membership based on capillary marketing by considering staffs experiences at Pak's pasteurized dairy in one month. The purpose of this study is to reduce the costs of the company along with the increase in sales. Constraints affecting target functions such as minimum sales per employee and maximum overtime days are also considered. The computational experiment by GAMS software demonstrates the effectiveness of the model in reaching its objectives.