scholarly journals Allocating Freight Empty Cars in Railway Networks with Dynamic Demands

2014 ◽  
Vol 2014 ◽  
pp. 1-12 ◽  
Author(s):  
Ce Zhao ◽  
Lixing Yang ◽  
Shukai Li
Keyword(s):  
Genetic Algorithm ◽  
Optimization Model ◽  
Numerical Experiments ◽  
Transportation Cost ◽  
Allocation Problem ◽  
Total Cost ◽  
Storage Cost ◽  
Proposed Model ◽  
Railway Networks

This paper investigates the freight empty cars allocation problem in railway networks with dynamic demands, in which the storage cost, unit transportation cost, and demand in each stage are taken into consideration. Under the constraints of capacity and demand, a stage-based optimization model for allocating freight empty cars in railway networks is formulated. The objective of this model is to minimize the total cost incurred by transferring and storing empty cars in different stages. Moreover, a genetic algorithm is designed to obtain the optimal empty cars distribution strategies in railway networks. Finally, numerical experiments are given to show the effectiveness of the proposed model and algorithm.

scholarly journals Optimization Model and Algorithm of Empty Pallets Dispatching under the Time-Space Network of Express Shipment

2018 ◽  
Vol 2018 ◽  
pp. 1-9 ◽  
Author(s):  
Kang Zhou ◽  
Shiwei He ◽  
Rui Song ◽  
Xiaole Guo ◽  
Kaiming Li
Keyword(s):  
Genetic Algorithm ◽  
Optimization Model ◽  
Clonal Selection ◽  
Transportation Cost ◽  
Transport Cost ◽  
Utilization Rate ◽  
Time Requirement ◽  
Total Cost ◽  
Time Space ◽  
The Cost

Relying on the express freight network, the dispatching of empty pallets based on the pallet pool mode is studied to reuse pallets with the minimum transport cost, enhance the pallet utilization rate, reduce the waste of resources, and save the cost of logistics. Considering the influence of transport efficiency for different modes in transportation process, differences of transportation cost, carbon emissions, and transportation timeliness of demand points required, an optimization model is constructed. The objective of the model is to minimize the total cost including transportation cost, inventory cost, lease cost, and loss cost. According to the structural characteristics of the model, genetic algorithm and improved cloud clonal selection operation is used to solve the model. Finally, the validity and rationality of the optimization model are verified by a case study. The result shows that the total dispatching cost of considering time requirement is 1.8 times the cost without considering the time requirement, respectively, both less than the total cost of pallets leasing. Moreover, when there are 3 supply points and 2 demand points and the number of iterations is 100, after the algorithms are run for 30 times, the worst values are 9305 and 8317 for genetic algorithm and the improved cloud clonal selection operation, respectively. Therefore, the efficiency of the improved cloud clonal selection operation is higher than genetic algorithm.

Routing Optimization of City Distribution Considering Access Restriction

2014 ◽  
Vol 505-506 ◽  
pp. 959-966 ◽  
Author(s):  
Xin Jin ◽  
Yang Tang ◽  
Qi Xu
Keyword(s):  
Genetic Algorithm ◽  
Optimization Model ◽  
Numerical Experiments ◽  
Benchmark Problems ◽  
Local Authorities ◽  
Urban Freight ◽  
Routing Optimization ◽  
Proposed Model ◽  
Urban Freight Transport ◽  
Negative Impacts

Nowadays, urban freight transport has become one of the most significant contributors to congestion and pollution. To combat these negative impacts, local authorities implement some restrictive regulations imposed on logistic enterprises about the time and area to which their vehicles can access. Under this circumstance, this paper constructed a city distribution routing optimization model considering access restriction. A Genetic Algorithm was proposed to solve the model. Numerical experiments based on the Solomons benchmark problems proved the effectiveness of the proposed model and algorithms.

scholarly journals Integrated Harvest and Farm-to-Door Distribution Scheduling with Postharvest Quality Deterioration for Vegetable Online Retailing

Agronomy ◽  
2019 ◽  
Vol 9 (11) ◽  
pp. 724
Author(s):  
Yiping Jiang ◽  
Bei Bian ◽  
Lingling Li
Keyword(s):  
Genetic Algorithm ◽  
Numerical Experiments ◽  
Programming Model ◽  
Time Windows ◽  
Sensitivity Analyses ◽  
Postharvest Quality ◽  
Online Retailing ◽  
Quality Deterioration ◽  
Distribution Scheduling ◽  
Proposed Model

With the rise of vegetable online retailing in recent years, the fulfillment of vegetable online orders has been receiving more and more attention. This paper addresses an integrated optimization model for harvest and farm-to-door distribution scheduling for vegetable online retailing. Firstly, we capture the perishable property of vegetables, and model it as a quadratic postharvest quality deterioration function. Then, we incorporate the postharvest quality deterioration function into the integrated harvest and farm-to-door distribution scheduling and formulate it as a quadratic vehicle routing programming model with time windows. Next, we propose a genetic algorithm with adaptive operators (GAAO) to solve the model. Finally, we carry out numerical experiments to verify the performance of the proposed model and algorithm, and report the results of numerical experiments and sensitivity analyses.

A Bi-Objective Order Allocation Optimization Model for Horizontal Manufacturing Collaborative Alliance

2010 ◽  
Vol 102-104 ◽  
pp. 836-840 ◽  
Author(s):  
Fang Qi Cheng
Keyword(s):  
Genetic Algorithm ◽  
Optimization Model ◽  
Optimal Solution ◽  
Order Allocation ◽  
Nsga Ii ◽  
Manufacturing Enterprises ◽  
Proposed Model ◽  
Optimal Solution Set ◽  
Simulation Results ◽  
Enterprise Community

Horizontal manufacturing collaborative alliance is a dispersed enterprise community consisting of several enterprises which produce the same kind of products. To correctly assign order among member companies of horizontal manufacturing collaborative alliance is one of the most important ways to improve the agility and competitiveness of manufacturing enterprises. For the order allocation problem, a bi-objective optimization model is developed to minimize the comprehensive cost and balance the production loads among the selected manufacturing enterprises. Non-dominated sorting genetic algorithm (NSGA-II) is applied to solve the optimization functions. The optimal solution set of Pareto is obtained. The simulation results indicate that the proposed model and algorithm is able to obtain satisfactory solutions.

Optimizing the Prefabrication Finishing Level in Modular Construction

2020 ◽  
Author(s):  
Mohammad Almashaqbeh ◽  
Khaled El-Rayes
Keyword(s):  
Optimization Model ◽  
Construction Projects ◽  
Transportation Cost ◽  
Healthcare Facility ◽  
Modular Construction ◽  
Structural Wall ◽  
Total Cost ◽  
Wide Range ◽  
Structural Frame

Prefabricated modules in modular construction projects can have a wide range of finishing levels that range from partially completed with only structural frame to fully completed with all structural, wall, mechanical, electrical, finishing and furnishing components. A higher module finishing level increases the offsite fabrication and transportation cost and decreases onsite assembly cost and duration while a lower finishing level produces the opposite results. This paper presents an optimization model that enables construction planners to identify an optimal finishing level for prefabricated modules in order to minimize the total cost of modular construction projects that includes all offsite fabrication, transportation, and onsite assembly costs. A case study of a modular construction project for a healthcare facility was analyzed to illustrate the use of the model and evaluate its performance. The results of this analysis highlight the original capabilities of the model in minimizing the total cost of modular construction projects.

scholarly journals Optimal re-allocation of mooring areas for yachts

2019 ◽  
Vol 4 (1) ◽  
pp. 94-105
Author(s):  
Shuaian Wang ◽  
Ran Yan ◽  
Lingxiao Wu ◽  
Dong Yang
Keyword(s):  
Optimization Model ◽  
Numerical Experiments ◽  
Design Methodology ◽  
Mathematical Optimization ◽  
Content Type ◽  
Integer Programing ◽  
Proposed Model ◽  
Quantitative Manner ◽  
Mathematical Optimization Model ◽  
The Government

Purpose The purpose of this study is to propose a mathematical optimization model to solve the yacht mooring area re-allocation problem (YMARP). The objective of the problem is to allow the maximum number of yachts to be moored at their ideal mooring areas. Design/methodology/approach In this paper, the YMARP is introduced, formally defined and discussed. The authors develop a 0-1 integer programing optimization model for the problem, which can be solved efficiently using off-shelf solvers. The performance of the model is tested on extensive numerical experiments. Findings The results of the numerical experiments demonstrate that the proposed model can solve the YMARP very efficiently using off-shelf solvers like CPLEX. In particular, problems with up to 30,000 yachts and 400 mooring areas can be solved to optimum within 30 s. Originality/value This study is one of the preliminary studies to consider problems arising in yacht management in a quantitative manner. The proposed model has three main merits. First, it enables the government to better manage yachts and mooring areas. Second, with more yacht owners assigned with ideal mooring areas, the model helps reduce the traveling time of the yacht owners to yacht mooring areas. Third, by reducing the traveling time of the yacht owners, the model contributes to lessening the traffic burden in cities.

Adaptive multi-objective traffic signal control using NLRMNSGA-II algorithm

2018 ◽  
Vol 45 (11) ◽  
pp. 973-985
Author(s):  
Yuan-Yang Zou ◽  
Xue-Guo Xu ◽  
Gui-Hua Lin
Keyword(s):  
Genetic Algorithm ◽  
Optimization Model ◽  
Efficient Algorithm ◽  
Numerical Experiments ◽  
Adaptive System ◽  
Signal Control ◽  
Traffic Signal Control ◽  
Multi Objective Optimization ◽  
New Model ◽  
Multi Objective

In this paper, we consider an adaptive system for controlling green times at junction. For this adaptive system, we present a multi-objective optimization model, which is much easier to solve than some existing models. Furthermore, to solve the new model, we suggest an algorithm, called NLRMNSGA-II, which is based on the nonlinear least regression and a modified non-dominated sorting genetic algorithm. Our numerical experiments indicate that the NLRMNSGA-II is an efficient algorithm for the considered adaptive system.

scholarly journals A Novel E-Commerce Negotiation Optimization Model Based on Improved Genetic Algorithm

2012 ◽  
Vol 6-7 ◽  
pp. 566-570
Author(s):  
Yang Liu
Keyword(s):  
Genetic Algorithm ◽  
Electronic Commerce ◽  
Value Creation ◽  
Optimization Model ◽  
Improved Genetic Algorithm ◽  
Model Based ◽  
Proposed Model ◽  
Business Market ◽  
Major Player ◽  
The Relationship

Electronic commerce has rapidly become a major player in the business market .This paper proposes a new electronic commerce negotiation optimization model based on improved genetic algorithm which depends on not only price, but also other factors of commodity. The proposed model illustrates the relationship between the business components required to support the e-commerce processes with the value creation factor and the controlling complexity. The experiment results show that the proposed algorithm can gain the optimal negotiation result more efficiently than other three kinds of negotiation algorithms in competitive bilateral multi-issue negotiation.

Job-Shop Scheduling on Exhibition Logistics Based on Genetic Algorithms

2013 ◽  
Vol 475-476 ◽  
pp. 1019-1024
Author(s):  
Zhi Gang Chen ◽  
Tao Yang ◽  
He Hua Li
Keyword(s):  
Genetic Algorithm ◽  
Genetic Algorithms ◽  
Job Shop ◽  
Job Shop Scheduling ◽  
Transportation Cost ◽  
Total Cost ◽  
Shop Scheduling ◽  
Logistics Service ◽  
Set Up ◽  
And Storage

The exhibition logistics, which generally deals with set-up, breakdown, transport, and storage to ensure that all specific exhibition requirements are met. It is very special from traditional logistics service that its transportation distant is very short and transportation cost can almost be ignored. To address the problems. a modal to optimize the total cost of exhibition logistics provider was proposed in this paper. Firstly the framwork of exhibition logistics was illustrated by a job-shop schedule modal. Secondly we used genetic algorithm (GA) to deal with problem of job shop scheduling. Finally the experiment result indicate that the proposed algorithm is feasible and effiective for this problem.

A Hybrid Genetic Algorithm for Production Capacity Allocation Problem with Multiple Regional Demands in Supply Chain

2014 ◽  
Vol 945-949 ◽  
pp. 3107-3111
Author(s):  
Zhen Wang ◽  
Lei Huang
Keyword(s):  
Genetic Algorithm ◽  
Mathematical Model ◽  
Supply Chain ◽  
Hybrid Genetic Algorithm ◽  
Production Capacity ◽  
Experimental Tests ◽  
Capacity Allocation ◽  
Allocation Problem ◽  
Proposed Model

Concentrating on the supplier with limited production capacity in supply chain, this paper established a mathematical model for production capacity allocation problem with consideration of multiple regional demands. The genetic algorithm is employed as solution mainframe in which a heuristics rule is developed to initiate the population and an elite pool is adopted to store those solutions with outstanding fitness values. The experimental tests show that the proposed model and algorithm are feasible and effective.

Sign in / Sign up

Export Citation Format

Share Document