scholarly journals Model and Algorithm for Container Allocation Problem with Random Freight Demands in Synchromodal Transportation

2015 ◽  
Vol 2015 ◽  
pp. 1-13 ◽  
Author(s):  
Yan Xu ◽  
Chengxuan Cao ◽  
Bin Jia ◽  
Guangzhi Zang
Keyword(s):  
Hybrid Algorithm ◽  
Numerical Experiments ◽  
Programming Model ◽  
Transportation Network ◽  
Capacity Allocation ◽  
Allocation Problem ◽  
Operational Level ◽  
Proposed Model ◽  
Encode Method ◽  
Effectiveness And Efficiency

This paper aims to investigate container allocation problem with random freight demands in synchromodal transportation network from container carriers’ perspective. Firstly, the problem is formulated as a stochastic integer programming model where the overall objective is to determine a container capacity allocation plan at operational level, so that the expected total transportation profit is maximized. Furthermore, by integrating simulated annealing with genetic algorithm, a problem-oriented hybrid algorithm with a novel gene encode method is designed to solve the optimization model. Some numerical experiments are carried out to demonstrate the effectiveness and efficiency of the proposed model and algorithm.

scholarly journals Integrated Optimization on Assortment Packing and Collaborative Shipping for Fashion Clothing

2018 ◽  
Vol 2018 ◽  
pp. 1-10
Author(s):  
Qianying Wang ◽  
Yiping Jiang ◽  
Yang Liu
Keyword(s):  
Numerical Experiments ◽  
Optimization Problem ◽  
Programming Model ◽  
Social Resources ◽  
Mixed Integer ◽  
Integrated Optimization ◽  
Proposed Model ◽  
Integer Nonlinear Programming ◽  
Nonlinear Programming Model ◽  
Effectiveness And Efficiency

With the diversification of customer’s demand and the shortage of social resources, meeting diverse requirements of customers and reducing logistics costs have attracted great attention in logistics area. In this paper, we address an integrated optimization problem that combines fashion clothing assortment packing with collaborative shipping simultaneously. We formulate this problem as a mixed integer nonlinear programming model (MINLP) and then convert the proposed model into a simplified model. We use LINGO 11.0 to solve the transformed model. Numerical experiments have been conducted to verify the effectiveness and efficiency of the proposed model, and the numerical results show that the proposed model is beneficial to the fashion clothing assortment packing and collaborative shipping planning.

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.

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.

scholarly journals Two-Stage Multiobjective Optimization for Emergency Supplies Allocation Problem under Integrated Uncertainty

2016 ◽  
Vol 2016 ◽  
pp. 1-13 ◽  
Author(s):  
Xuejie Bai
Keyword(s):  
Programming Model ◽  
Fuzzy Random Variable ◽  
Random Variable ◽  
Optimization Method ◽  
Allocation Problem ◽  
Two Stage ◽  
Whole Process ◽  
Proposed Model ◽  
Goal Programming Model ◽  
Computational Difficulty

This paper proposes a new two-stage optimization method for emergency supplies allocation problem with multisupplier, multiaffected area, multirelief, and multivehicle. The triplet of supply, demand, and the availability of path is unknown prior to the extraordinary event and is descriptive with fuzzy random variable. Considering the fairness, timeliness, and economical efficiency, a multiobjective expected value model is built for facility location, vehicle routing, and supply allocation decisions. The goals of proposed model aim to minimize the proportion of demand nonsatisfied and response time of emergency reliefs and the total cost of the whole process. When the demand and the availability of path are discrete, the expected values in the objective functions are converted into their equivalent forms. When the supply amount is continuous, the equilibrium chance in the constraint is transformed to its equivalent one. To overcome the computational difficulty caused by multiple objectives, a goal programming model is formulated to obtain a compromise solution. Finally, an example is presented to illustrate the validity of the proposed model and the effectiveness of the solution method.

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 Berth Allocation and Quay Crane Assignment Under Uncertainties

2020 ◽  
Author(s):  
Caimao Tan ◽  
Junliang He ◽  
Yuancai Wang
Keyword(s):  
Stochastic Programming ◽  
Numerical Experiments ◽  
Programming Model ◽  
Berth Allocation ◽  
Berth Allocation Problem ◽  
Operations Planning ◽  
Proposed Model ◽  
Departure Time ◽  
Stochastic Programming Model ◽  
Quay Crane Assignment

The integration of berth allocation problem (BAP) and quay crane assignment problem (QCAP) is an cardinal seaside operations planning, which is susceptible to uncertainties, e.g. uncertain vessels arrival and maritime market. This paper addresses the integrated optimization of BAP and QCAP under uncertainties. A stochastic programming model is formulated for minimizing the waiting time and delay departure time of vessels. Besides, numerical experiments and scenario analysis are conducted to validate the effectiveness of the proposed model.

scholarly journals A Study of Network Violator Interception Based on a Reliable Game Model

2014 ◽  
Vol 2014 ◽  
pp. 1-8 ◽  
Author(s):  
Shi An ◽  
Jianxun Cui ◽  
Meng Zhao ◽  
Jian Wang
Keyword(s):  
Simulated Annealing ◽  
Numerical Experiments ◽  
Programming Model ◽  
Choice Model ◽  
Transportation Network ◽  
Game Model ◽  
Planning Model ◽  
Binary Integer Programming ◽  
Objective Function Values ◽  
Expected Benefits

This study focuses on planning interceptor locations in a general transportation network to maximize the expected benefits from catching violators mixing in public traveler flow. Two reliability-related characteristics are also integrated into the planning model to make it more practical. One is that each interceptor (e.g., a sensor or a checkpoint) has a failure probability. The second is the existence of a “game” between the interceptor planner and violators. A nonlinear nonconvex binary integer programming model is presented. We develop a simulated annealing (SA) algorithm to solve this model, and numerical experiments are conducted to illustrate the computational efficiency of the proposed algorithm. We also analyze the sensitivity of the disruption probability of interceptors to optimal objective function values and discuss how to determine the values of these parameters in a violator route choice model.

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.

scholarly journals Scheduling for yard cranes based on two-stage hybrid dynamic programming

Transport ◽  
2016 ◽  
Vol 33 (2) ◽  
pp. 408-417
Author(s):  
Zhan Bian ◽  
Qi Xu ◽  
Na Li ◽  
Zhihong Jin
Keyword(s):  
Dynamic Programming ◽  
Hybrid Algorithm ◽  
Numerical Experiments ◽  
Handling Time ◽  
Container Terminals ◽  
Two Stage ◽  
Space Network ◽  
Time Space ◽  
Proposed Model ◽  
Visiting Time

Making operational plans for Yard Cranes (YCs) to enhance port efficiency has become vital issues for the container terminals. This paper discusses the load-scheduling problem of multiple YCs. The problem is to schedule two YCs at different container blocks, which serve the loading operations of one quay crane so as to minimize the total distance of visiting paths and the make-span at stack area. We consider the container handling time, the YC visiting time, and the waiting time of each YC when evaluating the make-span of the loading operation by YCs. Both the container bay visiting sequences and the number of containers picked up at each visit of the two YCs are determined simultaneously. A mathematical model, which considers interference between adjacent YCs, is provided by means of time-space network to formulate the problem and a two-stage hybrid algorithm composed of greedy algorithm and dynamic programming is developed to solve the proposed model. Numerical experiments were conducted to compare performances of the algorithm in this study with actual scheduling rules.

scholarly journals Modeling of Emergency Supply Scheduling Problem Based on Reliability and Its Solution Algorithm under Variable Road Network after Sudden-Onset Disasters

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-15 ◽  
Author(s):  
Tinggui Chen ◽  
Shiwen Wu ◽  
Jianjun Yang ◽  
Guodong Cong ◽  
Gongfa Li
Keyword(s):  
Road Network ◽  
Road Networks ◽  
Sudden Onset ◽  
The Road ◽  
Bee Colony ◽  
Proposed Model ◽  
Effectiveness And Efficiency ◽  
In Transit ◽  
Emergency Supply

It is common that many roads in disaster areas are damaged and obstructed after sudden-onset disasters. The phenomenon often comes with escalated traffic deterioration that raises the time and cost of emergency supply scheduling. Fortunately, repairing road network will shorten the time of in-transit distribution. In this paper, according to the characteristics of emergency supplies distribution, an emergency supply scheduling model based on multiple warehouses and stricken locations is constructed to deal with the failure of part of road networks in the early postdisaster phase. The detailed process is as follows. When part of the road networks fail, we firstly determine whether to repair the damaged road networks, and then a model of reliable emergency supply scheduling based on bi-level programming is proposed. Subsequently, an improved artificial bee colony algorithm is presented to solve the problem mentioned above. Finally, through a case study, the effectiveness and efficiency of the proposed model and algorithm are verified.

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