scholarly journals Flexible Optimization of International Shipping Routes considering Carbon Emission Cost

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Yao Yu ◽  
Jincheng Tu ◽  
Kun Shi ◽  
Mei Liu ◽  
Jihong Chen
Keyword(s):  
Carbon Emission ◽  
Single Port ◽  
Optimization Method ◽  
Effective Measure ◽  
Transportation Demand ◽  
International Shipping ◽  
Short Line ◽  
Ocean Shipping ◽  
Total Profit ◽  
The Cost

Carbon emissions cost is a potential effective measure to restrict hydrocarbon pollution in the international shipping trade. The minimization of the total cost is pursued by ship operators, whereas voyage cost is increasingly involving the replacement of clean fuel and changing the cost of the shipping route. A flexible optimization method focusing on maximizing the total profit is developed in terms of sailing speed optimization and single port skips integrate carbon emission influence. An actual ocean shipping route from Shanghai to Rotterdam is applied to validate the effectiveness of the proposed models. The results have shown that the shipping route profit is volatile along with the sailing speed and the number of port calls. However, the profit will be maximized when applying the single port skip and will slow down the sailing speed at the same time. The demand of planned skip port can be supported by a short line container. A system composed of ocean container liner and short line container can improve the profit by 4.05% and reduce the carbon emission by 19.70%. Furthermore, sensitive results show that the profit is less affected by the changing of the carbon emission cost. A small size container has enough ability to solve the short transportation demand in adjacent ports and convert extraberthing cost into profit. These findings can provide reliable support for the shipping route decision process considering future carbon emission costs.

scholarly journals Cost-Effectiveness of an Exercise Programme that Provided Group or Individual Training to Reduce the Fall Risk in Healthy Community-Dwelling People Aged 65–80: A Secondary Data Analysis

Healthcare ◽  
2021 ◽  
Vol 9 (6) ◽  
pp. 714
Author(s):  
Isaac Aranda-Reneo ◽  
Laura Albornos-Muñoz ◽  
Manuel Rich-Ruiz ◽  
María Ángeles Cidoncha-Moreno ◽  
Ángeles Pastor-López ◽  
...  
Keyword(s):  
Economic Evaluation ◽  
Cost Effectiveness ◽  
Older People ◽  
Incremental Cost ◽  
Fall Risk ◽  
Community Dwelling ◽  
Effective Measure ◽  
The Individual ◽  
The Cost ◽  
Individual Training

Research has demonstrated that some exercise programs are effective for reducing fall rates in community-dwelling older people; however, the literature is limited in providing clear recommendations of individual or group training as a result of economic evaluation. The objective of this study was to assess the cost-effectiveness of the Otago Exercise Program (OEP) for reducing the fall risk in healthy, non-institutionalized older people. An economic evaluation of a multicenter, blinded, randomized, non-inferiority clinical trial was performed on 498 patients aged over 65 in primary care. Participants were randomly allocated to the treatment or control arms, and group or individual training. The program was delivered in primary healthcare settings and comprised five initial sessions, ongoing encouragement and support to exercise at home, and a reinforcement session after six months. Our hypothesis was that the patients who received the intervention would achieve better health outcomes and therefore need lower healthcare resources during the follow-up, thus, lower healthcare costs. The primary outcome was the incremental cost-effectiveness ratio, which used the timed up and go test results as an effective measure for preventing falls. The secondary outcomes included differently validated tools that assessed the fall risk. The cost per patient was USD 51.28 lower for the group than the individual sessions in the control group, and the fall risk was 10% lower when exercises had a group delivery. The OEP program delivered in a group manner was superior to the individual method. We observed slight differences in the incremental cost estimations when using different tools to assess the risk of fall, but all of them indicated the dominance of the intervention group. The OEP group sessions were more cost-effective than the individual sessions, and the fall risk was 10% lower.

scholarly journals An Adaptive Optimization Method Based on Learning Rate Schedule for Neural Networks

2021 ◽  
Vol 11 (2) ◽  
pp. 850
Author(s):  
Dokkyun Yi ◽  
Sangmin Ji ◽  
Jieun Park
Keyword(s):  
Artificial Intelligence ◽  
Cost Function ◽  
Numerical Experiments ◽  
Global Minimum ◽  
Optimization Method ◽  
Learning Method ◽  
Adaptive Optimization ◽  
The Cost ◽  
Proof Of Convergence ◽  
Learning Data

Artificial intelligence (AI) is achieved by optimizing the cost function constructed from learning data. Changing the parameters in the cost function is an AI learning process (or AI learning for convenience). If AI learning is well performed, then the value of the cost function is the global minimum. In order to obtain the well-learned AI learning, the parameter should be no change in the value of the cost function at the global minimum. One useful optimization method is the momentum method; however, the momentum method has difficulty stopping the parameter when the value of the cost function satisfies the global minimum (non-stop problem). The proposed method is based on the momentum method. In order to solve the non-stop problem of the momentum method, we use the value of the cost function to our method. Therefore, as the learning method processes, the mechanism in our method reduces the amount of change in the parameter by the effect of the value of the cost function. We verified the method through proof of convergence and numerical experiments with existing methods to ensure that the learning works well.

scholarly journals Optimal Pricing Decisions for a Low-Carbon Supply Chain Considering Fairness Concern under Carbon Quota Policy

2021 ◽  
Vol 18 (2) ◽  
pp. 556
Author(s):  
Hao Zou ◽  
Jin Qin ◽  
Bo Dai
Keyword(s):  
Emission Reduction ◽  
Carbon Emission ◽  
Reduction Rate ◽  
Retail Price ◽  
Low Carbon ◽  
Close Attention ◽  
Carbon Emission Reduction ◽  
Carbon Supply ◽  
Total Profit ◽  
Fairness Concern

This research investigates the effect of fairness concerns on a sustainable low-carbon supply chain (LCSC) with a carbon quota policy, in which a manufacturer is in charge of manufacturing low-carbon products and sells them to a retailer. The demand is affected by price and the carbon emission reduction rate. The optimal decisions of pricing and carbon emission reduction rate are analyzed under four decision models: (i) centralized decision, (ii) decentralized decision without fairness concern, (iii) decentralized decision with manufacturer’s fairness concern, (iv) decentralized decision with retailer’s fairness concern. The results indicate that the profits in the centralized LCSC are higher than those in the decentralized LCSC with fairness concern. If a manufacturer pays close attention to fairness, the fairness concern coefficient will reduce the carbon emission reduction rate and the profit of the LCSC and increase the wholesale price and the retail price of the product. If a retailer pays close attention to fairness, and the preference of consumers for a low-carbon product is low, the fairness concern coefficient of the retailer increases the total profit of the LCSC and decreases the carbon emission reduction rate and retail price of the product. Otherwise, if the preference of consumers for a low-carbon product is great, the fairness concern coefficient of the retailer would lead to a lower retail price compared with the retail price in the centralized decision and decrease the total profit of the LCSC.

scholarly journals The Role of the Discount Policy of Prepayment on Environmentally Friendly Inventory Management

2022 ◽  
Vol 6 (1) ◽  
pp. 26
Author(s):  
Shirin Sultana ◽  
Abu Hashan Md Mashud ◽  
Yosef Daryanto ◽  
Sujan Miah ◽  
Adel Alrasheedi ◽  
...  
Keyword(s):  
Inventory Management ◽  
Emission Reduction ◽  
Carbon Emission ◽  
Positive Impact ◽  
Environmentally Friendly ◽  
Selling Price ◽  
Business Systems ◽  
Carbon Emission Reduction ◽  
Demand Rate ◽  
Total Profit

Nowadays, more and more consumers consider environmentally friendly products in their purchasing decisions. Companies need to adapt to these changes while paying attention to standard business systems such as payment terms. The purpose of this study is to optimize the entire profit function of a retailer and to find the optimal selling price and replenishment cycle when the demand rate depends on the price and carbon emission reduction level. This study investigates an economic order quantity model that has a demand function with a positive impact of carbon emission reduction besides the selling price. In this model, the supplier requests payment in advance on the purchased cost while offering a discount according to the payment in the advanced decision. Three different types of payment-in-advance cases are applied: (1) payment in advance with equal numbers of instalments, (2) payment in advance with a single instalment, and (3) the absence of payment in advance. Numerical examples and sensitivity analysis illustrate the proposed model. Here, the total profit increases for all three cases with higher values of carbon emission reduction level. Further, the study finds that the profit becomes maximum for case 2, whereas the selling price and cycle length become minimum. This study considers the sustainable inventory model with payment-in-advance settings when the demand rate depends on the price and carbon emission reduction level. From the literature review, no researcher has undergone this kind of study in the authors’ knowledge.

Optimization of Multistage Machining Systems, Part 1: Mathematical Solution

1992 ◽  
Vol 114 (4) ◽  
pp. 524-531 ◽  
Author(s):  
J. S. Agapiou
Keyword(s):  
Optimization Problem ◽  
Cutting Parameters ◽  
Optimization Method ◽  
Idle Time ◽  
Optimization Techniques ◽  
Machining Parameters ◽  
Machining Time ◽  
Physical Constraints ◽  
Time Requirements ◽  
The Cost

The optimization problem for multistage machining systems has been investigated. Due to uneven time requirements at different stages in manufacturing, there could be idle times at various stations. It may be advantageous to reduce the values of machining parameters in order to reduce the cost at stations that require less machining time. However, optimization techniques available through the literature do not effectively utilize the idle time for the different stations generated during the balancing of the system. Proposed in this paper is an optimization method which utilizes the idle time to the full extent at all machining stations, with the intention of improving tool life and thus achieving cost reduction. The mathematical analysis considers the optimization of the production cost with an equality constraint of zero idle time for the stations with idle time. Physical constraints regarding the cutting parameters, force, power, surface finish, etc., as they arise in different operations, are also considered. The aforementioned problem has been theoretically analyzed and a computational algorithm developed. The advantages and effectiveness of the proposed approach are finally established through an example.

Convergence of Simulated Annealing with Feedback Temperature Schedules

1997 ◽  
Vol 11 (3) ◽  
pp. 279-304 ◽  
Author(s):  
M. Kolonko ◽  
M. T. Tran
Keyword(s):  
Simulated Annealing ◽  
Cost Function ◽  
Job Shop ◽  
Job Shop Scheduling ◽  
Optimization Method ◽  
Search Process ◽  
Local Optimum ◽  
Fixed Sequence ◽  
Temperature Parameter ◽  
The Cost

It is well known that the standard simulated annealing optimization method converges in distribution to the minimum of the cost function if the probability a for accepting an increase in costs goes to 0. α is controlled by the “temperature” parameter, which in the standard setup is a fixed sequence of values converging slowly to 0. We study a more general model in which the temperature may depend on the state of the search process. This allows us to adapt the temperature to the landscape of the cost function. The temperature may temporarily rise such that the process can leave a local optimum more easily. We give weak conditions on the temperature schedules such that the process of solutions finally concentrates near the optimal solutions. We also briefly sketch computational results for the job shop scheduling problem.

A Robust Optimization Method for Systems With Significant Nonlinear Effects

1993 ◽  
Author(s):  
Jyh-Cheng Yu ◽  
Kosuke Ishii
Keyword(s):  
Heat Treatment ◽  
Robust Optimization ◽  
Nonlinear Effects ◽  
Optimization Method ◽  
Post Heat Treatment ◽  
Worst Case ◽  
Estimation Scheme ◽  
Optimization Methodology ◽  
Major Factors ◽  
The Cost

Abstract This paper describes a robust optimization methodology for design involving either complex simulations or actual experiments. The proposed procedure optimizes the worst case response that consists of a weighted sum of expected mean and response variance. The estimation scheme for expected mean and variance adopts the modified 3-point Gauss quadrature integration to assure superior accuracy for systems with significant nonlinear effects. We apply the proposed method to the robust design of geometric parameters of heat treated parts to minimize the cost of post heat treatment operations. The paper investigates the major factors influencing geometric distortions due to heat treatment and the rules of thumb in design. The study focuses on relating dimensional distortion to the design of part geometry. To illustrate the utility of the proposed method, we present the formulation of a case study on allocation of dimensions of preheat treated (green) shafts to minimize the cost of post heat treatment operations. The final result is not presented yet pending the completion of further experiments.

Snapshot of Personnel Productivity Assessment in Indian IT Industry

2012 ◽  
pp. 220-234
Author(s):  
Thamaraiselvan Natarajan ◽  
Saraswathy R. Aravinda Rajah ◽  
Sivagnanasundaram Manikavasagam
Keyword(s):  
Illustrative Case ◽  
It Industry ◽  
Productivity Measurement ◽  
Effective Measure ◽  
Case Examples ◽  
Common Criteria ◽  
Training Programmes ◽  
The Cost ◽  
Work Done ◽  
Productivity Assessment

Measuring the productivity of employees has been one of the concerns of IT organisations globally. It is indispensable to calculate the cost of the project vis-a-vis the time estimate. While calculating the lines of coding (Loc) has generally been the common criteria for programmers, it is not always considered an effective measure of the actual work done. The time spent on activities like attending training programmes, participating in meetings, co-coordinating with colleagues, or conceptualising, is presumably unaccounted. Questions lurking unanswered relate to the effective criteria and international benchmarks. Amusingly most companies have their own home-grown productivity calculators to track the progress of their projects. Productivity measurement is equally important for an organisation as well as an IT worker. Awareness of productivity paves way-for mutual progress-self and the organization. This paper, through illustrative-case examples, provides a holistic perspective of personnel productivity assessment methods used in Indian IT industry.

scholarly journals Tax or Subsidy? Optimal Carbon Emission Policy: A Supply Chain Perspective

2020 ◽  
Vol 12 (4) ◽  
pp. 1548 ◽  
Author(s):  
Xing Yin ◽  
Xiaolin Chen ◽  
Xiaolin Xu ◽  
Lianmin Zhang
Keyword(s):  
Supply Chain ◽  
Carbon Emission ◽  
Negative Impact ◽  
Green Technology ◽  
Manufacturing Firm ◽  
Numerical Studies ◽  
The Social ◽  
The Government ◽  
Increasing Demand ◽  
The Cost

With a rigid requirement for environment protection, governments need to make appropriate policies to induce firms to adopt green technology in consideration of the rapidly increasing demand for environmentally friendly products. We investigated the government policy from the perspective of a supply chain, which consisted of the upstream government (she) and the downstream manufacturing firm (he). The government decided on the policy (tax or subsidy) to maximize the social welfare, while the firm decided on the greenness level of the product, which affects the consumers’ choice behavior and hence his own demand. Assuming else being equal, the government should adopt the tax policy if consumers are very sensitive to the greenness, the cost of greening is high, or the negative impact due to carbon emission is large, and subsidize the firm otherwise. We also conduct some numerical studies when price is endogenous. The main insights can be carried over.

An enhanced spatial statistical method for continuous monitoring of winter road surface conditions

2020 ◽  
Vol 47 (10) ◽  
pp. 1154-1165 ◽  
Author(s):  
Lian Gu ◽  
Mingjian Wu ◽  
Tae J. Kwon
Keyword(s):  
Continuous Monitoring ◽  
Model Performance ◽  
Optimization Method ◽  
Road Surface ◽  
Estimation Errors ◽  
Winter Maintenance ◽  
Surface Conditions ◽  
Modified Particle Swarm Optimization ◽  
The Cost ◽  
Kriging Estimation

To facilitate more efficient winter maintenance decision support, road weather information systems (RWIS) have been widely used by highway agencies. However, the cost of RWIS stations is high, and they have limited monitoring coverage. To address this challenge, this paper presents an innovative framework that applies regression kriging to integrate stationary and mobile RWIS data to improve the accuracy of road surface temperature (RST) estimation. Furthermore, an optimal RWIS network expansion strategy is introduced by incorporating a modified particle swarm optimization method with the objective of minimizing spatially averaged kriging estimation errors. A sensitivity analysis is also conducted to investigate the influence of station densities on model performance. The case study from Alberta, Canada, demonstrates the feasibility and applicability of the proposed method. The findings provide insights for continuous monitoring and visualization of both road weather and surface conditions and for optimizing RWIS network planning.

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