scholarly journals Scheduling Just-in-Time Transport Vehicles to Feed Parts for Mixed Model Assembly Lines

2020 ◽  
Vol 2020 ◽  
pp. 1-13 ◽  
Author(s):  
Yunfang Peng ◽  
Tian Zeng ◽  
Yajuan Han ◽  
Beixin Xia
Keyword(s):  
Large Scale ◽  
Assembly Line ◽  
Mixed Model ◽  
Programming Model ◽  
Primary Objective ◽  
Mixed Integer ◽  
Inventory Level ◽  
Just In Time ◽  
Time Model ◽  
Delivery Strategy

In order to solve the problem of vehicle scheduling to feed parts at automobile assembly line, this study proposes a just-in-time delivery method combined with the mode of material supermarket. A mixed integer linear programming model with the primary objective of using the least number of tow trains is constructed by considering capacity of vehicle and inventory levels of line. On the basis of the minimum number of tow trains, the schedule of each tour is reasonably planned to minimize inventory of assembly line, which is the secondary objective of the part supply problem. Additionally, a heuristic algorithm which can obtain a satisfactory solution in a short time is designed to solve large-scale problems after considering continuity and complexity of modern automobile production. Furthermore, some cases are analyzed and compared with the widely used periodic delivery strategy, and the feasibility of just-in-time model and algorithm is verified. The results reveal that just-in-time delivery strategy has more advantages in reducing inventory level than periodic delivery strategy.

scholarly journals A Branch-and-Price Algorithm for Balancing Two-Sided Assembly Lines with Zoning Constraints

2021 ◽  
Vol 2021 ◽  
pp. 1-18
Author(s):  
Qidong Yin ◽  
Xiaochuan Luo ◽  
Julien Hohenstein
Keyword(s):  
Large Scale ◽  
Manufacturing Industry ◽  
Assembly Line ◽  
Programming Model ◽  
Assembly Line Balancing ◽  
Mixed Integer ◽  
Branch And Price ◽  
Assembly Lines ◽  
Real World Datasets ◽  
Assembly Production

Two-sided assembly lines are widely used in the large-size product manufacturing industry, especially for automotive assembly production. Balancing the assembly line is significant for assembly process planning and assembly production. In this study, we develop a novel and exact method to optimize the two-sided assembly line balancing problem with zoning constraints (TALBz), in which the aim is to minimize the number of mated-stations considering the task restrictions. A mixed-integer programming model is employed to exactly describe the TALBz problem. To strengthen the computational efficiency, we apply Dantzig–Wolfe decomposition to reformulate the TALBz problem. We further propose a branch-and-price (B&P) algorithm that integrates the column generation approach into a branch-and-bound frame. Both the benchmark datasets with zoning constraints and without zoning constraints are tested to evaluate the performance of the B&P algorithm. The numerical results show that our proposed approach can obtain optimal solutions efficiently on most cases. In addition, experiments on the real-world datasets originating from passenger vehicle assembly lines are conducted. The proposed B&P algorithm shows its advantage in tackling practical problems with the task restrictions. This developed methodology therefore provides insight for solving large-scale TALBz problems in practice.

scholarly journals Multidepot Heterogeneous Vehicle Routing Problem for a Variety of Hazardous Materials with Risk Analysis

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Bochen Wang ◽  
Qiyuan Qian ◽  
Zheyi Tan ◽  
Peng Zhang ◽  
Aizhi Wu ◽  
...  
Keyword(s):  
Risk Analysis ◽  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Large Scale ◽  
Programming Model ◽  
Hazardous Materials ◽  
Mixed Integer ◽  
Small Scale ◽  
Routing Problem ◽  
Heterogeneous Vehicle Routing Problem

This study investigates a multidepot heterogeneous vehicle routing problem for a variety of hazardous materials with risk analysis, which is a practical problem in the actual industrial field. The objective of the problem is to design a series of routes that minimize the total cost composed of transportation cost, risk cost, and overtime work cost. Comprehensive consideration of factors such as transportation costs, multiple depots, heterogeneous vehicles, risks, and multiple accident scenarios is involved in our study. The problem is defined as a mixed integer programming model. A bidirectional tuning heuristic algorithm and particle swarm optimization algorithm are developed to solve the problem of different scales of instances. Computational results are competitive such that our algorithm can obtain effective results in small-scale instances and show great efficiency in large-scale instances with 70 customers, 30 vehicles, and 3 types of hazardous materials.

scholarly journals Supply chain optimization with variable demand by considering financial criteria and scenarios

2017 ◽  
Vol 26 (44) ◽  
pp. 21 ◽  
Author(s):  
John Willmer Escobar
Keyword(s):  
Supply Chain ◽  
Large Scale ◽  
Net Present Value ◽  
Programming Model ◽  
Supply Chain Design ◽  
Mixed Integer ◽  
Supply Network ◽  
Distribution Centers ◽  
Supply Chain Optimization ◽  
Starting Point

This paper contemplates the supply chain design problem of a large-scale company by considering the maximization of the Net Present Value. In particular, the variability of the demand for each type of product at each customer zone has been estimated. As starting point, this paper considers an established supply chain for which the main problem is to determine the decisions regarding expansion of distribution centers. The problem is solved by using a mixed-integer linear programming model, which optimizes the different demand scenarios. The proposed methodology uses a scheme of optimization based on the generation of multiple demand scenarios of the supply network. The model is based on a real case taken from a multinational food company, which supplies to the Colombian and some international markets. The obtained results were compared with the equivalent present costs minimization scheme of the supply network, and showed the importance and efficiency of the proposed approach as an alternative for the supply chain design with stochastic parameters.

scholarly journals A Multistage Solution Approach for Dynamic Reactive Power Optimization Based on Interval Uncertainty

2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Xiaodong Shen ◽  
Yang Liu ◽  
Yan Liu
Keyword(s):  
Large Scale ◽  
Reactive Power ◽  
Power Optimization ◽  
Programming Model ◽  
Nonconvex Programming ◽  
Interval Uncertainty ◽  
Mixed Integer ◽  
Reactive Power Optimization ◽  
Renewable Energy Resources ◽  
Integer Quadratic Programming

In order to solve the uncertainty and randomness of the output of the renewable energy resources and the load fluctuations in the reactive power optimization, this paper presents a novel approach focusing on dealing with the issues aforementioned in dynamic reactive power optimization (DRPO). The DRPO with large amounts of renewable resources can be presented by two determinate large-scale mixed integer nonlinear nonconvex programming problems using the theory of direct interval matching and the selection of the extreme value intervals. However, it has been admitted that the large-scale mixed integer nonlinear nonconvex programming is quite difficult to solve. Therefore, in order to simplify the solution, the heuristic search and variable correction approaches are employed to relax the nonconvex power flow equations to obtain a mixed integer quadratic programming model which can be solved using software packages such as CPLEX and GUROBI. The ultimate solution and the performance of the presented approach are compared to the traditional methods based on the evaluations using IEEE 14-, 118-, and 300-bus systems. The experimental results show the effectiveness of the presented approach, which potentially can be a significant tool in DRPO research.

scholarly journals Optimization of Continuous Berth Scheduling by Taking into Account Double-Line Ship Mooring

2020 ◽  
Vol 2020 ◽  
pp. 1-11 ◽  
Author(s):  
Cheng Luo ◽  
Hongying Fei ◽  
Dana Sailike ◽  
Tingyi Xu ◽  
Fuzhi Huang
Keyword(s):  
Large Scale ◽  
Programming Model ◽  
Minimum Cost ◽  
Pso Algorithm ◽  
Container Terminals ◽  
Mixed Integer ◽  
Double Line ◽  
Support Tool ◽  
Berth Scheduling ◽  
Operation Cost

“Double-Line Ship Mooring” (DLSM) mode has been applied as an initiative operation mode for solving berth allocation problems (BAP) in certain giant container terminals in China. In this study, a continuous berth scheduling problem with the DLSM model is illustrated and solved with exact and heuristic methods with an objective to minimize the total operation cost, including both the additional transportation cost for vessels not located at their minimum-cost berthing position and the penalties for vessels not being able to leave as planned. First of all, this problem is formulated as a mixed-integer programming model and solved by the CPLEX solver for small-size instances. Afterwards, a particle swarm optimization (PSO) algorithm is developed to obtain good quality solutions within reasonable execution time for large-scale problems. Experimental results show that DLSM mode can not only greatly reduce the total operation cost but also significantly improve the efficiency of berth scheduling in comparison with the widely used single-line ship mooring (SLSM) mode. The comparison made between the results obtained by the proposed PSO algorithm and that obtained by the CPLEX solver for both small-size and large-scale instances are also quite encouraging. To sum up, this study can not only validate the effectiveness of DLSM mode for heavy-loaded ports but also provide a powerful decision support tool for the port operators to make good quality berth schedules with the DLSM mode.

Network Design for Shipping Service of Large-Scale Intermodal Liners

2012 ◽  
Vol 2269 (1) ◽  
pp. 42-50 ◽  
Author(s):  
Qiang Meng ◽  
Shuaian Wang ◽  
Zhiyuan Liu
Keyword(s):  
Network Design ◽  
Large Scale ◽  
Programming Model ◽  
Transportation Network ◽  
Liner Shipping ◽  
Maritime Transportation ◽  
Mixed Integer ◽  
Hub And Spoke ◽  
Shipping Company ◽  
Proposed Model

A model was developed for network design of a shipping service for large-scale intermodal liners that captured essential practical issues, including consistency with current services, slot purchasing, inland and maritime transportation, multiple-type containers, and origin-to-destination transit time. The model used a liner shipping hub-and-spoke network to facilitate laden container routing from one port to another. Laden container routing in the inland transportation network was combined with the maritime network by defining a set of candidate export and import ports. Empty container flow is described on the basis of path flow and leg flow in the inland and maritime networks, respectively. The problem of network design for shipping service of an intermodal liner was formulated as a mixed-integer linear programming model. The proposed model was used to design the shipping services for a global liner shipping company.

Sign in / Sign up

Export Citation Format

Share Document