scholarly journals Solving the order batching and sequencing problem with multiple pickers: A grouped genetic algorithm

2021 ◽  
Vol 11 (3) ◽  
pp. 2516
Author(s):  
Jose Alejandro Cano ◽  
Pablo Cortés ◽  
Emiro Antonio Campo ◽  
Alexander Alberto Correa-Espinal
Keyword(s):  
Genetic Algorithm ◽  
Customer Service ◽  
Load Capacity ◽  
Operating Time ◽  
Distribution Centers ◽  
Operations Planning ◽  
Sequencing Problem ◽  
Order Batching ◽  
Feasible Solutions ◽  
First Time

This paper introduces a grouped genetic algorithm (GGA) to solve the order batching and sequencing problem with multiple pickers (OBSPMP) with the objective of minimizing total completion time. To the best of our knowledge, for the first time, an OBSPMP is solved by means of GGA considering picking devices with heterogeneous load capacity. For this, an encoding scheme is proposed to represent in a chromosome the orders assigned to batches, and batches assigned to picking devices. Likewise, the operators of the proposed algorithm are adapted to the specific requirements of the OBSPMP. Computational experiments show that the GGA performs much better than six order batching and sequencing heuristics, leading to function objective savings of 18.3% on average. As a conclusion, the proposed algorithm provides feasible solutions for the operations planning in warehouses and distribution centers, improving margins by reducing operating time for order pickers, and improving customer service by reducing picking service times.

Path optimization of CNC PCB drilling using hybrid Taguchi genetic algorithm

Kybernetes ◽  
2016 ◽  
Vol 45 (1) ◽  
pp. 107-125 ◽  
Author(s):  
Dony Hidayat Al-Janan ◽  
Tung-Kuan Liu
Keyword(s):  
Genetic Algorithm ◽  
Printed Circuit Boards ◽  
Numerical Control ◽  
Circuit Boards ◽  
Improved Genetic Algorithm ◽  
Solution Quality ◽  
Content Type ◽  
Neighbor Search ◽  
Feasible Solutions ◽  
The Traveling Salesman Problem

Purpose – In this study, the hybrid Taguchi genetic algorithm (HTGA) was used to optimize the computer numerical control-printed circuit boards drilling path. The optimization was performed by searching for the shortest route for the drilling path. The number of feasible solutions is exponentially related to the number of hole positions. The paper aims to discuss these issues. Design/methodology/approach – Therefore, a traveling cutting tool problem (TCP), which is similar to the traveling salesman problem, was used to evaluate the drilling path; this evaluation is considered an NP-hard problem. In this paper, an improved genetic algorithm embedded in the Taguchi method and a neighbor search method are proposed for improving the solution quality. The classical TCP problems proposed by Lim et al. (2014) were used for validating the performance of the proposed algorithm. Findings – Results showed that the proposed algorithm outperforms a previous study in robustness and convergence speed. Originality/value – The HTGA has not been used for optimizing the drilling path. This study shows that the HTGA can be applied to complex problems.

scholarly journals An improved Genetic Algorithm For Fuzzy Production PlanningProblems with Application

2015 ◽  
Vol 1 (3) ◽  
pp. 390
Author(s):  
Jalal Abdulkareem Sultan ◽  
Omar Ramzi Jasim ◽  
Sarmad Abdulkhaleq Salih
Keyword(s):  
Genetic Algorithm ◽  
Customer Service ◽  
Fundamental Problem ◽  
Demand Forecasting ◽  
Fuzzy Model ◽  
Main Idea ◽  
Production Schedule ◽  
Improved Genetic Algorithm ◽  
Customer Service Level ◽  
Master Production Schedule

Production Planning or Master Production Schedule (MPS) is a key interface between marketing and manufacturing, since it links customer service directly to efficient use of production resources. Mismanagement of the MPS is considered as one of fundamental problem in operation and it can potentially lead to poor customer satisfaction.  In this paper, an improved Genetic Algorithm (IGA) is used to solving fuzzy multi-objective master production schedule (FMOMPS). The main idea is to integrate GA with local search operator. The FMOMPS was applied in the Cotton and medical gauzes plant in Mosul city. The application involves determine the gross requirements by demand forecasting using artificial neural networks. The IGA proved its efficiency in solving MPS problems compared with the genetic algorithm for fuzzy and non-fuzzy model, as the results clearly showed the ability of IGA to determine intelligently how much, when, and where the additional capacities (overtimes) are required such that the inventory can be reduced without affecting customer service level.

scholarly journals A novel method to extract juglone from Juglans mandshurica waste branches using a water-in-oil microemulsion

2021 ◽  
Author(s):  
Chunying Li ◽  
Xianming Meng ◽  
Mengfei Tian ◽  
Shen Li ◽  
Yao Tian ◽  
...  
Keyword(s):  
Operating Time ◽  
Tween 80 ◽  
Microemulsion System ◽  
Microwave Assisted Extraction ◽  
Juglans Mandshurica ◽  
Microwave Assisted ◽  
Assisted Extraction ◽  
Low Efficiency ◽  
Ethanol Ethanol ◽  
First Time

Abstract Pruning of Juglans mandshurica produces a lot of waste branches which are potentially rich source of juglone. However, they are usually discarded as waste. Given that, the water-in-oil microemulsion was proposed, aiming at developing a novel and efficient microemulsion-based microwave-assisted extraction（MBMAE）method. By which juglone in the Juglans mandshurica waste branches could be obtained. In our experiment, the waste branches powder was added to the MBMAE system. Under the best microemulsion system: (tween 80: n-propanol : n-hexane : water＝27% : 13.5% : 4.5% : 55%), the PH of the microemulsion solution of 5.6, microemulsion - Juglans mandshurica branches powder of 20:1 (mL/g), operating temperature of 40°C and operating time of 63 s, operating power of 400 W, the juglone yield was 4.58 mg/g. The results were that the extraction yield applying the MBMAE method were 1.86-fold and 6.65-fold that of microwave-assisted extraction applying ethanol (Ethanol-MAE) and heat reflux extraction by ethanol (Ethanol-HRE), respectively. Obviously, the MBMAE method could be used as an alternative to traditional extraction methods to extract juglone.Statement of Novelty A large number of waste branches from Juglans mandshurica pruning are often discarded as waste. Based on the concept of green development, this work proposes for the first time the extraction and utilization of juglone from the waste branches of Juglans mandshurica. However, a certain problem such as low efficiency, high cost, and complicated operation is existing in traditional extraction method for juglone. Consequently, a special microemulsion system for juglone was established for the first time, and on this basis, the application of MBMAE method to the extraction of juglone was also proposed for the first time. It provides data support for the extraction of juglone from other materials or plants.

Performance of a Short Multi-Grooved Capillary Compensated Hydrostatic Journal Bearing

1968 ◽  
Vol 183 (16) ◽  
pp. 107-115
Author(s):  
J. K. Patrick ◽  
N. N. S. Chen
Keyword(s):  
Journal Bearing ◽  
Load Capacity ◽  
Flow Characteristics ◽  
Lubricating Oil ◽  
Load Carrying Capacity ◽  
Straight Line ◽  
Load Carrying ◽  
Capillary Type ◽  
First Time ◽  
Oil Film Pressure

This paper presents the results of an extensive experimental investigation into the performance of a short multi-grooved bearing subjected to a range of static and alternating loads. Lubricating oil was supplied, at pressures of up to 2000 lb/in2, to capillary type restrictors connected to 10 closed-end axial grooves in the bearing. The bearing had a length/diameter ratio of 1/3 and operated with a journal speed and load frequency of 327 c/min. Measured load capacity, stiffness, and flow characteristics indicate that bearings of this type have a significant load-carrying capacity at zero journal speed and that the load capacity is increased by journal rotation. A feature of the journal behaviour under alternating loads is the movement of the journal centre along a straight line coincident with the load plane. The extensive oil film pressure surveys indicate for the first time the pressure distribution within narrow hydrostatic bearings and provide a basis for a realistic theoretical analysis of this type of bearing.

Empathy in non-altruistic settings: Conceptualization and operationalization in business

2021 ◽  
Author(s):  
Mainak Bhattacharya
Keyword(s):  
Customer Service ◽  
English Language ◽  
Research Work ◽  
Measurement Scales ◽  
Managerial Decision ◽  
Mental Processes ◽  
Business Outcomes ◽  
Business Studies ◽  
Stakeholder Interaction ◽  
First Time

A hundred years since the first mention of the word empathy in the English language, scientists and philosophers have been unable to arrive at a common consensus on its precise definition. Common wisdom associates empathy with vicarious emotional arousal or altruism. This study conducts a systematic review of research work in business studies dealing with empathy. The method used comprises applying lower-level abstract taxonomy to empathy, for the first time, in external business stakeholder interaction situations of sales, marketing, and customer service. The measurement scales used in the studies are analyzed to showcase mental processes at stake during the act of empathy, the theorized functions, and expected business outcomes of empathy. Implications are drawn for various aspects of managerial decision making. The study suggests a novel framework to execute a more nuanced grade examination of processes involved in empathy and reducing subjectivity in conceptual definitions. The study also calls for overhauling empathy measurement scales, mainly to suit adaptations in empirical business studies.

Beyond 1-1 Advising

2015 ◽  
pp. 162-175
Author(s):  
Dawna Wilson ◽  
Kimberly M. Lowry
Keyword(s):  
High School ◽  
Customer Service ◽  
Workforce Development ◽  
Support Services ◽  
First Century ◽  
Career And Technical ◽  
Business Partners ◽  
Advising Model ◽  
First Time ◽  
First Time In College

This chapter presents practices Eastfield College employs to move beyond a traditional one-on-one advising model when preparing students for the twenty-first century workforce. No matter the students' status, first-time in college, returning to retool or dual high school-college enrollee, community colleges must rethink approaches to supporting them throughout the workforce development process if we are to adequately meet this century's workforce demands. In an institution-wide, customer-service approach, student needs not only drive the design but the delivery of support services. This chapter describes how Eastfield takes services to students by hosting Lunch and Learns, providing onsite advising, and establishing liaisons with local business partners. Collaborations with area high school districts to facilitate career and technical related career offerings are also discussed.

A Heuristic Approach for Disassembly Sequencing Problem for Robotic Disassembly Operations

2012 ◽  
pp. 438-447
Author(s):  
Ahmed ElSayed ◽  
Elif A. Kongar ◽  
Surendra M. Gupta
Keyword(s):  
Genetic Algorithm ◽  
Value Added ◽  
Recovery Process ◽  
Electronic Products ◽  
Sequencing Problem ◽  
Material Recovery ◽  
Disassembly Sequence ◽  
Robotic Disassembly ◽  
Efficient Recovery ◽  
Disassembly Sequencing

Electronic products enter the waste stream rapidly due to technological enhancements. Their parts and material recovery involve significant economic and environmental gain. To regain the value added to such products a certain level of disassembly may be required. Disassembly operations are often expensive and the complexity of determining the best disassembly sequence increases as the number of parts in a product grows. Therefore, it is necessary to develop methodologies for obtaining optimal or near optimal disassembly sequences to ensure efficient recovery process. To that end, this chapter introduces a Genetic Algorithm based methodology to develop disassembly sequencing for end-of-life products. A numerical example is presented to provide and demonstrate better understating and functionality of the algorithm.

scholarly journals A Multilayer Genetic Algorithm for Automated Guided Vehicles and Dual Automated Yard Cranes Coordinated Scheduling

2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Qianru Zhao ◽  
Shouwen Ji ◽  
Wenpeng Zhao ◽  
Xinling De
Keyword(s):  
Genetic Algorithm ◽  
Energy Consumption ◽  
Operating Time ◽  
Operation Time ◽  
Complex Model ◽  
Automated Guided Vehicles ◽  
Total Energy Consumption ◽  
Equipment Operation ◽  
Storage Location ◽  
Calculation Results

At present, a lot of studies on automatic terminal scheduling are aimed at the shortest operating time. An effective way to reduce the operating time is to increase the amount of operating equipment. However, people often ignore the additional costs and energy consumption caused by increasing the amount of equipment. This paper comprehensively considers the two aspects of the equipment operation time and equipment quantity matching. With the minimum total energy consumption of the operating equipment as the objective function, a cooperative scheduling model of Automated Guided Vehicles (AGVs) and dual Automated Yard Cranes (AYCs) is established. In the modelling process, we also considered the interference problem between dual Automated Yard Cranes (AYCs). In order to solve this complex model, this paper designs an improved multilayer genetic algorithm. Finally, the calculation results from CPLEX and a multilayer genetic algorithm are compared, and the effectiveness of the model and algorithm is proved by experiments. In addition, at the same time, it is proved that it is necessary to consider the interference problem of dual Automated Yard Cranes (AYCs), and the optimal quantity matching scheme for the equipment and the optimal temporary storage location is given.

scholarly journals A GPU-Enabled Compact Genetic Algorithm for Very Large-Scale Optimization Problems

Mathematics ◽  
2020 ◽  
Vol 8 (5) ◽  
pp. 758
Author(s):  
Andrea Ferigo ◽  
Giovanni Iacca
Keyword(s):  
Genetic Algorithm ◽  
Large Scale ◽  
Optimization Problems ◽  
Search Space ◽  
Large Scale Problems ◽  
Processing Power ◽  
Compact Genetic Algorithm ◽  
Estimation Of Distribution ◽  
Feasible Solutions ◽  
Compact Optimization

The ever-increasing complexity of industrial and engineering problems poses nowadays a number of optimization problems characterized by thousands, if not millions, of variables. For instance, very large-scale problems can be found in chemical and material engineering, networked systems, logistics and scheduling. Recently, Deb and Myburgh proposed an evolutionary algorithm capable of handling a scheduling optimization problem with a staggering number of variables: one billion. However, one important limitation of this algorithm is its memory consumption, which is in the order of 120 GB. Here, we follow up on this research by applying to the same problem a GPU-enabled “compact” Genetic Algorithm, i.e., an Estimation of Distribution Algorithm that instead of using an actual population of candidate solutions only requires and adapts a probabilistic model of their distribution in the search space. We also introduce a smart initialization technique and custom operators to guide the search towards feasible solutions. Leveraging the compact optimization concept, we show how such an algorithm can optimize efficiently very large-scale problems with millions of variables, with limited memory and processing power. To complete our analysis, we report the results of the algorithm on very large-scale instances of the OneMax problem.

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