Parallel Assembly Lines with Heterogeneous Workforce: A Cost-Driven Mathematical Model and Simulated Annealing Approach

2021 ◽  
pp. 99-112
Author(s):  
Serhan Kökhan ◽  
Ömer Faruk Baykoç
Keyword(s):  
Mathematical Model ◽  
Simulated Annealing ◽  
Assembly Lines ◽  
Parallel Assembly ◽  
Heterogeneous Workforce

Concurrent scheduling and layout of virtual manufacturing cells considering assembly aspects

2020 ◽  
pp. 095440542098068
Author(s):  
Kamran Forghani ◽  
S. M. T. Fatemi Ghomi ◽  
Reza Kia
Keyword(s):  
Mathematical Model ◽  
Simulated Annealing ◽  
Model Material ◽  
Virtual Manufacturing ◽  
Superior Performance ◽  
Shop Floor ◽  
Processing Route ◽  
Manufacturing Cells ◽  
Comparison Results ◽  
Virtual Manufacturing Cells

Cell formation, scheduling, and facility layout are three main decisions in designing manufacturing cells. In this paper, we address the integration of these decisions in virtual manufacturing cells considering assembly aspects and process routing. We develop a mathematical model to determine the machine cells, the layout of machines and workstations on the shop floor, the processing route of parts, and the production sequence of operations on the machines. In this mathematical model, material handling costs and cycle time are minimized. To the best of our knowledge, this is the first paper that concurrently addresses the scheduling and layout of virtual manufacturing cells with assembly aspects and so-called criteria. To effectively solve the problem, a Population-based Simulated Annealing (PSA) combined with linear programming is proposed. The practical usability of the developed model is demonstrated in a case study. Finally, instances from the literature are solved to evaluate the performance of the PSA. The comparison results showed the superior performance of the PSA in comparison with CPLEX solver and standard simulated annealing.

Performance Evaluation of Hybrid Photovoltaic Thermal Thermoelectric Collector Using Grasshopper Optimization Algorithm With Simulated Annealing

2020 ◽  
Vol 142 (6) ◽  
Author(s):  
Anmol Gupta ◽  
Sanjay Agrawal ◽  
Yash Pal
Keyword(s):  
Mathematical Model ◽  
Performance Evaluation ◽  
Simulated Annealing ◽  
Optimization Algorithm ◽  
Single Channel ◽  
Electrical Energy ◽  
Average Value ◽  
Grasshopper Optimization Algorithm ◽  
Mass Flowrate ◽  
Grasshopper Optimization

Abstract In this paper, a mathematical model of a single-channel photovoltaic thermal (PVT) air collector incorporated with a thermoelectric (TE) module has been presented. The overall electrical energy obtained from the photovoltaic thermal-thermoelectric (PVT-TE) collector is 5.78% higher than the PVT collector. Further, the grasshopper optimization algorithm (GOA) and hybrid grasshopper optimization algorithm with simulated annealing (GOA-SA) have been proposed and implemented to optimize the parameters of opaque PVT-TE collector. Although there are different parameters that influence the performance of PVT-TE system, yet in this study only four parameters, viz., length of the channel (L), width of the channel (b), mass flowrate of air in the channel (mair), and temperature of air at the inlet of channel (Tair,i) are considered for optimization. The simulation result demonstrates that the hybrid GOA-SA algorithm turned out to be an exceptionally effective method for optimal tuning of the parameters of the PVT-TE system. The result explicitly shows that the average value of overall electrical efficiency and exergy gain are 15.27% and 27.0565 W, respectively, when the parameters are optimized by the suggested GOA-SA algorithm which is way ahead with respect to the outcomes obtained with that of the calculated values or using GOA algorithm alone.

A Model for Shortening the Length of Activities in Construction and Overhaul Planning: UPROB

2002 ◽  
Author(s):  
Niko Majdandzˇic´ ◽  
Slavko Sebastijanovic´ ◽  
Gordana Maticˇevic´ ◽  
Nebojsˇa Sebastijanovic´
Keyword(s):  
Mathematical Model ◽  
Thermal Energy ◽  
Input Data ◽  
Critical Path ◽  
Planning System ◽  
Task Completion ◽  
Assembly Lines ◽  
Total Cost ◽  
Activity Cost ◽  
Optimal Variation

This paper presents a mathematical model of the UPROB (planning system for construction and overhaul) system that was developed for tank assembly lines, construction of thermal energy structures, and for performing an overhaul in complex plants. Planning technology includes utilizing linear diagrams with a direct usage of input data from a plant’s database. A model has been developed to determine the critical path and also, to define steps for the most economical shortening of the entire plan. Several plan variations are developed (according to specified goals) and the management determines the optimal variation. After selecting a plan, it is possible to control and create work orders for individual tasks in certain activities. Task completion percentage, activity cost, and the total cost of the plan are also provided.

scholarly journals Mathematical Model for Proactive Resequencing of Mixed Model Assembly Lines

2019 ◽  
Vol 33 ◽  
pp. 438-445
Author(s):  
Achim Kampker ◽  
Kai Kreisköther ◽  
Marius Schumacher
Keyword(s):  
Mathematical Model ◽  
Mixed Model ◽  
Assembly Lines ◽  
Mixed Model Assembly Lines ◽  
Mixed Model Assembly

Balancing of parallel assembly lines

2006 ◽  
Vol 103 (2) ◽  
pp. 600-609 ◽  
Author(s):  
Hadi Gökçen ◽  
Kürşad Ağpak ◽  
Recep Benzer
Keyword(s):  
Assembly Lines ◽  
Parallel Assembly

scholarly journals Research on airport multi-objective optimization of stand allocation based on simulated annealing algorithm

2021 ◽  
Vol 18 (6) ◽  
pp. 8314-8330
Author(s):  
Ningning Zhao ◽  
◽  
Mingming Duan
Keyword(s):  
Mathematical Model ◽  
Simulated Annealing ◽  
Objective Function ◽  
Simulated Annealing Algorithm ◽  
Allocation Scheme ◽  
Multi Objective Optimization ◽  
Practical Application ◽  
Allocation Decision ◽  
Multi Objective ◽  
Annealing Algorithm

<abstract> <p>In this study, a multi-objective optimized mathematical model of stand pre-allocation is constructed with the shortest travel distance for passengers, the lowest cost for airlines and the efficiency of stand usage as the overall objectives. The actual data of 12 flights at Lanzhou Zhongchuan Airport are analyzed by application and solved by simulated annealing algorithm. The results of the study show that the total objective function of the constructed model allocation scheme is reduced by 40.67% compared with the actual allocation scheme of the airport, and the distance traveled by passengers is reduced by a total of 4512 steps, while one stand is saved and the efficiency of stand use is increased by 31%, in addition to the reduction of airline cost by 300 RMB. In summary, the model constructed in the study has a high practical application value and is expected to be used for airport stand pre-allocation decision in the future.</p> </abstract>

scholarly journals Optimal vehicle route schedules in picking up and delivering cargo containers considering time windows in logistics distribution networks: A case study

2020 ◽  
Vol 26 (4) ◽  
pp. 174-184
Author(s):  
Thi Diem Chau Le ◽  
Duy Duc Nguyen ◽  
Judit Oláh ◽  
Miklós Pakurár
Keyword(s):  
Mathematical Model ◽  
Simulated Annealing ◽  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Time Windows ◽  
Distribution Networks ◽  
Mixed Integer ◽  
Vehicle Group ◽  
Real Problem ◽  
Routing Problem

AbstractThis study describes a pickup and delivery vehicle routing problem, considering time windows in reality. The problem of tractor truck routes is formulated by a mixed integer programming model. Besides this, three algorithms - a guided local search, a tabu search, and simulated annealing - are proposed as solutions. The aims of our study are to optimize the number of internal tractor trucks used, and create optimal routes in order to minimize total logistics costs, including the fixed and variable costs of an internal vehicle group and the renting cost of external vehicles. Besides, our study also evaluates both the quality of solutions and the time to find optimal solutions to select the best suitable algorithm for the real problem mentioned above. A novel mathematical model is formulated by OR tools for Python. Compared to the current solution, our results reduced total costs by 18%, increased the proportion of orders completed by internal vehicles (84%), and the proportion of orders delivered on time (100%). Our study provides a mathematical model with time constraints and large job volumes for a complex distribution network in reality. The proposed mathematical model provides effective solutions for making decisions at logistics companies. Furthermore, our study emphasizes that simulated annealing is a more suitable algorithm than the two others for this vehicle routing problem.

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