scholarly journals Joint Optimization of a Dry Port with Multilevel Location and Container Transportation: The Case of Northeast China

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-16
Author(s):  
Feng Pian ◽  
Qiuju Shi ◽  
Xue Yao ◽  
Huiling Zhu ◽  
Weixin Luan
Keyword(s):  
Northeast China ◽  
Transportation Cost ◽  
Joint Optimization ◽  
Container Transportation ◽  
Total Cost ◽  
The Road ◽  
Total Transportation Cost ◽  
The Cost ◽  
Port Construction ◽  
Dry Ports

Dry port construction can reduce the cost of container transportation, and its location is the focus of existing research. Considering dry port capacity limitations and scale advantages, this study calculates the costs associated with dry port construction and operations, transportation, time, and the environment and constructs a joint optimization model of the dry port location and transportation scheme to minimize the total cost. Taking 35 prefecture-level cities in Northeast China as the source of container goods and Dalian port as the destination, this study conducts an empirical analysis using the Gurobi 9.0.2 optimizer of the AMPL software to solve the problem and takes the minimum total cost as the goal to select the best dry port and container transshipment scheme. The research draws the following conclusions. Seven dry ports also need to be built in the road-rail (RD-RL) mode, which shares 82.76% of the container transshipment volume, to reduce the total transportation cost by approximately 21.67%. Although multimodal transport through dry ports increases the time cost slightly, it can significantly reduce the economic and environmental costs of container transportation.

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.

Evaluation of Tread Wear

1952 ◽  
Vol 25 (2) ◽  
pp. 321-330 ◽  
Author(s):  
Dietrich G. Stechert ◽  
Thomas D. Bolt
Keyword(s):  
Regression Line ◽  
Total Cost ◽  
Rapid Turnover ◽  
The Road ◽  
Truck Tire ◽  
Tire Wear ◽  
Different Types ◽  
Road Testing ◽  
The Cost

Abstract The observed existence of a linear log-log relationship between nonskid loss and mileage in a great number of widely different types of tests may be exploited in order to realize substantial savings in the road testing of tires for tread wear. In many evaluations it is common practice for the Gates Rubber Co. to test tires to one half initial nonskid depth or to some arbitrary mileage only. The regression line and mileage to baldness are then determined. Of course, the greater the amount of data, and the more accurately controlled the conditions of testing, the more reliable will be the mileage to baldness. If in tread wear evaluations tests were terminated prior to baldness, about $180 could be saved for each passenger tire tested, and $490 for each truck tire, for every 10,000 miles. One investigation, to determine the effect of three different tire designs on tread wear, was made at a total cost of $2200. If all tires had been tested to baldness, the cost would have been approximately $4600. In comparison with former common practice, the application of the proposed method of analysis of tire wear measurements can result in more reliable tread wear evaluations, more economical utilization of the tire test fleet, and a more rapid turnover of ideas.

scholarly journals Dynamic Optimization Technique for Distribution of Goods with Stochastic Shortages

2013 ◽  
Vol 2013 ◽  
pp. 1-12
Author(s):  
Charles I. Nkeki
Keyword(s):  
Optimal Control ◽  
Dynamic Optimization ◽  
Error Bounds ◽  
Optimization Technique ◽  
Transportation Cost ◽  
Maximum Error ◽  
Expected Cost ◽  
Total Cost ◽  
The Cost ◽  
In Transit

This work considers the distribution of goods with stochastic shortages from factories to stores. It is assumed that in the process of shipping the goods to various stores, some proportion of the goods will be damaged (which will lead to shortage of goods in transit). The cost of the damaged goods is added to the cost of the shipment. A proportion of the total expected cost of the shortage goods is assumed to be recovered and should be deducted from the total cost of the shipment. In order to determine the minimum transportation costs for the operation, we adopt dynamic optimization principles. The optimal transportation cost and optimal control policies of shipping the goods from factories to stores were obtained. We find that the optimal costs of the goods recovered could be determined. It was further found that the optimum costs of distributing the goods with minimum and maximum error bounds coincide only at infinity.

scholarly journals Routing cross-docking depots, considering the time windows and pricing routes (case study: container transportation of Chabahar port)

2020 ◽  
Vol 33 (02) ◽  
pp. 409-422
Author(s):  
Farhad Bavar ◽  
Majid Sabzehparvar ◽  
Mona Ahmadi Rad
Keyword(s):  
High Efficiency ◽  
Programming Model ◽  
Time Windows ◽  
Container Transportation ◽  
Total Cost ◽  
Cross Docking ◽  
Proposed Model ◽  
Nonlinear Programming Model ◽  
Implementation Time ◽  
The Cost

In this study, we develop a model for routing cross-docking centers considering time windows and pricing routs. In this model picking and delivery in several times is permitted and each knot can be serviced by more than one vehicle. Every truck can transport one or more product, in other words, we consider compatibility between product and vehicle. This model includes two goals: reducing the total cost and reducing the cost of carrying goods (freight fare). The total cost includes the cost required to traverse between the points, the cost of traversing the routes between the central cross-docking center and the first points after moving, and the cost to traverse the routes between the last points in each route and the depots that must be minimized. In general, the purpose of the model is to obtain the number of cross-docking center, the number of vehicles and the best route in the distribution network. We present a nonlinear programming model for this problem. We have solved the proposed model by GAMS. As the dimensions of the problem increase, the implementation time of the program increases progressively. So, in order to solve the model in medium and large scales, we proposed a genetic meta-heuristic algorithm. The results of examining different issues by the meta-heuristic approach show the very high efficiency of the developed algorithms in terms of the solution time and the answer of the problem.

On Solving Fuzzy Multi-Objective Multi-Choice Stochastic Transportation Problems

2019 ◽  
pp. 332-378
Keyword(s):  
Probability Distributions ◽  
Transportation Cost ◽  
Transportation Problems ◽  
Multi Objective ◽  
Fuel Prices ◽  
Product Availability ◽  
Road Congestion ◽  
Total Transportation Cost ◽  
Cost Parameters ◽  
The Cost

This chapter presents solution procedures for solving unbalanced multi-objective multi-choice stochastic transportation problems in a hybrid fuzzy uncertain environment. In this chapter, various types of unbalanced multi-objective fuzzy stochastic transportation models are considered with the assumption that the parameters representing supplies of the products at the origins and demands of the products at the destinations, capacity of the conveyances, associated with the system constraints are either fuzzy numbers (FNs) or fuzzy random variables (FRVs) with some known continuous fuzzy probability distributions. The multi-choice cost parameters are considered as FNs. In this chapter, two objectives are considered: total transportation cost and total transportation time. As the transportation cost mainly depends on fuel prices and since fuel prices are highly fluctuating, the cost parameters are taken as multi-choice cost parameters with possibilistic uncertain nature. The time of transportation mainly depends on vehicle conditions, quality of roads, and road congestion. Due to these uncertain natures, the parameters representing time of transportation are also taken as fuzzy uncertain multi-choice parameters. In this transportation model, these objectives are minimized satisfying the constraints: product availability constraints, requirement of the product constraints, and capacity of the conveyance constraints. Numerical examples are provided for the sake of illustration of the methodology presented in this chapter, and also achieved solutions are compared with the solutions obtained by some existing methodologies to establish its effectiveness.

scholarly journals Determination of the Safest Route for Logging Trucks Based on Road Types and Conditions

2020 ◽  
Vol 3 (1) ◽  
pp. 5
Author(s):  
Abdullah E. Akay
Keyword(s):  
Transportation Cost ◽  
Forest Products ◽  
Complex Problem ◽  
Forest Road ◽  
The Road ◽  
Mountainous Regions ◽  
On The Road ◽  
Total Transportation Cost ◽  
Alternative Routes ◽  
Logging Truck

Hauling of wood-based forest products is a complex problem that requires evaluation of many alternative routes. Forest transportation has been generally done by using logging trucks with high carrying capacity. Logging truck driving is one of the dangerous occupations in forestry, particularly in Turkey, where forest lands are mostly located in mountainous regions with steep slopes. The safety risk of truck driving mainly depends on the road standards and conditions. The majority of the forest roads in Turkey have low standards that limit the maneuverability of logging trucks. In such conditions, forest transportation should be planned by considering not only transportation costs but also the safety of logging truck driving. In this study, the GIS-based network analysis method was used to develop the optimum transportation plans for two scenarios. In the first scenario, an optimum plan that minimized the total transportation cost was developed, while a transportation plan that ensured the safest logging truck driving was optimized in the second scenario. A safety score was assigned to each road section based on the road type (asphalt, gravel, forest road) and road conditions (good, medium, poor). In the study area, located in the city of Bursa in Turkey, there were three forest depots and five landings. The results indicated that the transportation cost increased by 15.76% when the safety of logging truck driving was prioritized. In this scenario, forest products from three landings were transported to different depots, compared to the first scenario.

OPTIMAL FEASIBLE SOLUTIONS TO A ROAD FREIGHT TRANSPORTATION PROBLEM

2020 ◽  
Vol 5 (1) ◽  
pp. 456
Author(s):  
Tolulope Latunde ◽  
Joseph Oluwaseun Richard ◽  
Opeyemi Odunayo Esan ◽  
Damilola Deborah Dare
Keyword(s):  
Transportation Problem ◽  
Optimal Solution ◽  
Transportation Cost ◽  
North West ◽  
Life Problems ◽  
Basic Feasible Solutions ◽  
Feasible Solutions ◽  
Road Freight Transportation ◽  
The Cost ◽  
Cost Of Transportation

For twenty decades, there is a visible ever forward advancement in the technology of mobility, vehicles and transportation system in general. However, there is no "cure-all" remedy ideal enough to solve all life problems but mathematics has proven that if the problem can be determined, it is most likely solvable. New methods and applications will keep coming to making sure that life problems will be solved faster and easier. This study is to adopt a mathematical transportation problem in the Coca-Cola company aiming to help the logistics department manager of the Asejire and Ikeja plant to decide on how to distribute demand by the customers and at the same time, minimize the cost of transportation. Here, different algorithms are used and compared to generate an optimal solution, namely; North West Corner Method (NWC), Least Cost Method (LCM) and Vogel’s Approximation Method (VAM). The transportation model type in this work is the Linear Programming as the problems are represented in tables and results are compared with the result obtained on Maple 18 software. The study shows various ways in which the initial basic feasible solutions to the problem can be obtained where the best method that saves the highest percentage of transportation cost with for this problem is the NWC. The NWC produces the optimal transportation cost which is 517,040 units.

The estimated healthcare cost of diabetic retinopathy in Indonesia and its projection for 2025

2019 ◽  
Vol 104 (4) ◽  
pp. 487-492 ◽  
Author(s):  
Muhammad Bayu Sasongko ◽  
Firman Setya Wardhana ◽  
Gandhi Anandika Febryanto ◽  
Angela Nurini Agni ◽  
Supanji Supanji ◽  
...  
Keyword(s):  
Diabetic Retinopathy ◽  
Laser Treatment ◽  
Healthcare Cost ◽  
Cost Of Illness ◽  
Public Health Intervention ◽  
Transportation Cost ◽  
Population Based ◽  
State Budget ◽  
Illness Model ◽  
The Cost

PurposeTo estimate the total healthcare cost associated with diabetic retinopathy (DR) in type 2 diabetes in Indonesia and its projection for 2025.MethodsA prevalence-based cost-of-illness model was constructed from previous population-based DR study. Projection for 2025 was derived from estimated diabetes population in 2025. Direct treatment costs of DR were estimated from the perspective of healthcare. Patient perspective costs were obtained from thorough interview including only transportation cost and lost of working days related to treatment. We developed four cost-of-illness models according to DR severity level, DR without necessary treatment, needing laser treatment, laser +intravitreal (IVT) injection and laser + IVT +vitrectomy. All costs were estimated in 2017 US$.ResultsThe healthcare costs of DR in Indonesia were estimated to be $2.4 billion in 2017 and $8.9 billion in 2025. The total cost in 2017 consisted of the cost for no DR and mild–moderate non-proliferative DR (NPDR) requiring eye screening ($25.9 million), severe NPDR or proliferative DR (PDR) requiring laser treatment ($0.25 billion), severe NPDR or PDR requiring both laser and IVT injection ($1.75 billion) and advance level of PDR requiring vitrectomy ($0.44 billion).ConclusionsThe estimated healthcare cost of DR in Indonesia in 2017 was considerably high, nearly 2% of the 2017 national state budget, and projected to increase significantly to more than threefold in 2025. The highest cost may incur for DR requiring both laser and IVT injection. Therefore, public health intervention to delay or prevent severe DR may substantially reduce the healthcare cost of DR in Indonesia.

scholarly journals The Development of Patient Scheduling Groups for an Effective Appointment System

2016 ◽  
Vol 07 (01) ◽  
pp. 43-58 ◽  
Author(s):  
Yu Li Huang
Keyword(s):  
Access To Care ◽  
Treatment Time ◽  
Optimization Technique ◽  
Urgent Care ◽  
Patient Scheduling ◽  
Total Cost ◽  
Patient Type ◽  
Clinic Efficiency ◽  
The Cost ◽  
The Impact

SummaryPatient access to care and long wait times has been identified as major problems in outpatient delivery systems. These aspects impact medical staff productivity, service quality, clinic efficiency, and health-care cost.This study proposed to redesign existing patient types into scheduling groups so that the total cost of clinic flow and scheduling flexibility was minimized. The optimal scheduling group aimed to improve clinic efficiency and accessibility.The proposed approach used the simulation optimization technique and was demonstrated in a Primary Care physician clinic. Patient type included, emergency/urgent care (ER/UC), follow-up (FU), new patient (NP), office visit (OV), physical exam (PE), and well child care (WCC). One scheduling group was designed for this physician. The approach steps were to collect physician treatment time data for each patient type, form the possible scheduling groups, simulate daily clinic flow and patient appointment requests, calculate costs of clinic flow as well as appointment flexibility, and find the scheduling group that minimized the total cost.The cost of clinic flow was minimized at the scheduling group of four, an 8.3% reduction from the group of one. The four groups were: 1. WCC, 2. OV, 3. FU and ER/UC, and 4. PE and NP. The cost of flexibility was always minimized at the group of one. The total cost was minimized at the group of two. WCC was considered separate and the others were grouped together. The total cost reduction was 1.3% from the group of one.This study provided an alternative method of redesigning patient scheduling groups to address the impact on both clinic flow and appointment accessibility. Balance between them ensured the feasibility to the recognized issues of patient service and access to care. The robustness of the proposed method on the changes of clinic conditions was also discussed.

scholarly journals A MEAN FIELD GAME ANALYSIS OF SIR DYNAMICS WITH VACCINATION

2020 ◽  
pp. 1-18
Author(s):  
Josu Doncel ◽  
Nicolas Gast ◽  
Bruno Gaujal
Keyword(s):  
Mean Field ◽  
Vaccination Strategy ◽  
Game Analysis ◽  
Total Cost ◽  
Mean Field Game ◽  
Vaccination Behavior ◽  
Switching Curve ◽  
The One ◽  
The Cost ◽  
Vaccination Period

We analyze a mean field game model of SIR dynamics (Susceptible, Infected, and Recovered) where players choose when to vaccinate. We show that this game admits a unique mean field equilibrium (MFE) that consists in vaccinating at a maximal rate until a given time and then not vaccinating. The vaccination strategy that minimizes the total cost has the same structure as the MFE. We prove that the vaccination period of the MFE is always smaller than the one minimizing the total cost. This implies that, to encourage optimal vaccination behavior, vaccination should always be subsidized. Finally, we provide numerical experiments to study the convergence of the equilibrium when the system is composed by a finite number of agents ( $N$ ) to the MFE. These experiments show that the convergence rate of the cost is $1/N$ and the convergence of the switching curve is monotone.

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