scholarly journals Economic Development Based on a Mathematical Model: An Optimal Solution Method for the Fuel Supply of International Road Transport Activity

Energies ◽  
2021 ◽  
Vol 14 (10) ◽  
pp. 2963
Author(s):  
Melinda Timea Fülöp ◽  
Miklós Gubán ◽  
György Kovács ◽  
Mihály Avornicului
Keyword(s):  
Decision Making ◽  
Ad Hoc ◽  
Market Competition ◽  
Optimal Solution ◽  
Cost Savings ◽  
Cost Effective ◽  
Optimization Method ◽  
Optimal Decision ◽  
Environmental Damage ◽  
Fuel Cost

Due to globalization and increased market competition, forwarding companies must focus on the optimization of their international transport activities and on cost reduction. The minimization of the amount and cost of fuel results in increased competition and profitability of the companies as well as the reduction of environmental damage. Nowadays, these aspects are particularly important. This research aims to develop a new optimization method for road freight transport costs in order to reduce the fuel costs and determine optimal fueling stations and to calculate the optimal quantity of fuel to refill. The mathematical method developed in this research has two phases. In the first phase the optimal, most cost-effective fuel station is determined based on the potential fuel stations. The specific fuel prices differ per fuel station, and the stations are located at different distances from the main transport way. The method developed in this study supports drivers’ decision-making regarding whether to refuel at a farther but cheaper fuel station or at a nearer but more expensive fuel station based on the more economical choice. Thereafter, it is necessary to determine the optimal fuel volume, i.e., the exact volume required including a safe amount to cover stochastic incidents (e.g., road closures). This aspect of the optimization method supports drivers’ optimal decision-making regarding optimal fuel stations and how much fuel to obtain in order to reduce the fuel cost. Therefore, the application of this new method instead of the recently applied ad-hoc individual decision-making of the drivers results in significant fuel cost savings. A case study confirmed the efficiency of the proposed method.

scholarly journals Development of an Optimization Method and Software for Optimizing Global Supply Chains for Increased Efficiency, Competitiveness, and Sustainability

2019 ◽  
Vol 11 (6) ◽  
pp. 1610
Author(s):  
György Kovács ◽  
Béla Illés
Keyword(s):  
Supply Chains ◽  
Service Providers ◽  
Market Competition ◽  
Cost Effective ◽  
Optimization Method ◽  
Global Market ◽  
Environmental Damage ◽  
Global Supply Chains ◽  
Design Constraint ◽  
Use Of Resources

Presently, an increasing human population, customer consumption, and global market competition result in the reduction of natural resources and growing environmental damage. Therefore, the current practice in the use of resources is not sustainable. The production companies have to focus not only on cost-effective and profitable operation, but at the same time environmentally friendly and sustainable production in order to increase competitiveness. New innovative technologies are required, improving the efficiency of the processes and the optimization of global supply chains (GSC) in order to establish sustainability in environmental, social, and economic aspects. The aim of the study is the GSCs’ optimization, which means forming the optimal combination of the chain members (suppliers, final assemblers, service providers) to achieve cost-effective, time-effective, and sustainable operation. This study introduces an elaborated single- and multi-objective optimization method, including the objective functions (cost, lead time) and design constraints (production and service capacities; volume of inventories; flexibility and sustainability of the chain members). Based on the elaborated method, software has been developed for the optimization of sustainable GSCs. The significance and novelty of the developed method and software is that the chain members have been required to fulfill the sustainability design constraint built into the software. A real case study is introduced, for the optimal design of a sustainable GSC, to confirm that our developed optimization method and software can be applied effectively in practice for the optimization of both profitable and sustainable GSCs.

The Nature Of Strategic-Decision-Making Models

2011 ◽  
pp. 241-271
Author(s):  
Tamio Shimizu ◽  
Marley Monteiro de Carvalho ◽  
Fernando Jose Barbin
Keyword(s):  
Decision Making ◽  
Goal Function ◽  
Optimization Method ◽  
Strategic Decision ◽  
Optimal Decision ◽  
Problem Solution ◽  
Goal Functions ◽  
Optimal Decision Making ◽  
The Individual ◽  
Optimum Solution

In the multiple goal function problems, there is no optimum solution fully satisfying all goals at the same time. The individual goal’s functions are, in general, conflicting and it is not possible to have an optimization method to solve the problem. There is usually a consensus solution satisfying minimal criteria of optimum values for each individual goal function. This consensus is based on the Pareto’s principle presented in chapter nine. The optimal decision making in problems with multiple goals will be analyzed at the end of this chapter (Goicoechea et al., 1982; Keeney & Raiffa, 1976; Dyson, 1990; Saaty, 1980, 1994; Bonabeau, 2003; Charan, 2001; Choo, 1998; Day et al., 1997). In considering restrictions across several scenarios, the problem solution becomes more difficult due to the high number of possible combinations of goal functions and scenarios to be considered.

scholarly journals Optimizing motor decision-making through competition with opponents

2018 ◽  
Author(s):  
Keiji Ota ◽  
Mamoru Tanae ◽  
Kotaro Ishii ◽  
Ken Takiyama
Keyword(s):  
Decision Making ◽  
Optimal Solution ◽  
Optimal Decision ◽  
Fine Motor ◽  
Risk Averse ◽  
Risk Seeking ◽  
Competitive Game ◽  
Ski Jumping ◽  
Human Motor ◽  
Optimal Decision Making

AbstractAlthough optimal decision-making is essential for sports performance and fine motor control, it has been repeatedly confirmed that humans show a strong risk-seeking bias, selecting a risky strategy over an optimal solution. Despite such evidence, the ideal method to promote optimal decision-making remains unclear. Here, we propose that interactions with other people can influence motor decision-making and improve risk-seeking bias. We developed a competitive reaching game (a variant of the “chicken game”) in which aiming for greater rewards increased the risk of no reward and subjects competed for the total reward with their opponent. The game resembles situations in sports, such as a penalty kick in soccer, service in tennis, the strike zone in baseball, or take-off in ski jumping. In five different experiments, we demonstrated that, at the beginning of the competitive game, the subjects robustly switched their risk-seeking strategy to a risk-averse strategy. Following the reversal of the strategy, the subjects achieved optimal decision-making when competing with risk-averse opponents. This optimality was achieved by a non-linear influence of an opponent’s decisions on a subject’s decisions. These results suggest that interactions with others can alter human motor decision strategies and that competition with a risk-averse opponent is key for optimizing motor decision-making.

scholarly journals Optimization Method of Power Equipment Maintenance Plan Decision-Making Based on Deep Reinforcement Learning

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Yanhua Yang ◽  
Ligang Yao
Keyword(s):  
Decision Making ◽  
Reinforcement Learning ◽  
Optimization Model ◽  
Power Grid ◽  
Optimization Method ◽  
Optimal Decision ◽  
Maintenance Cost ◽  
Equipment Maintenance ◽  
Safety Constraints ◽  
Maintenance Plan

The safe and reliable operation of power grid equipment is the basis for ensuring the safe operation of the power system. At present, the traditional periodical maintenance has exposed the abuses such as deficient maintenance and excess maintenance. Based on a multiagent deep reinforcement learning decision-making optimization algorithm, a method for decision-making and optimization of power grid equipment maintenance plans is proposed. In this paper, an optimization model of power grid equipment maintenance plan that takes into account the reliability and economics of power grid operation is constructed with maintenance constraints and power grid safety constraints as its constraints. The deep distributed recurrent Q-networks multiagent deep reinforcement learning is adopted to solve the optimization model. The deep distributed recurrent Q-networks multiagent deep reinforcement learning uses the high-dimensional feature extraction capabilities of deep learning and decision-making capabilities of reinforcement learning to solve the multiobjective decision-making problem of power grid maintenance planning. Through case analysis, the comparative results show that the proposed algorithm has better optimization and decision-making ability, as well as lower maintenance cost. Accordingly, the algorithm can realize the optimal decision of power grid equipment maintenance plan. The expected value of power shortage and maintenance cost obtained by the proposed method is $71.75$ $MW·H$ and $496000$ $yuan$.

scholarly journals Mathematical Apparatus of Optimal Decision-Making Based on Vector Optimization

2019 ◽  
Vol 2 (4) ◽  
pp. 32 ◽  
Author(s):  
Mashunin
Keyword(s):  
Mathematical Model ◽  
Decision Making ◽  
Vector Optimization ◽  
Optimal Solution ◽  
Problem Definition ◽  
Optimal Decision ◽  
Mathematical Apparatus ◽  
Optimal Decision Making ◽  
Definition Of ◽  
Priority Criterion

We present a problem of “acceptance of an optimal solution” as a mathematical model in the form of a vector problem of mathematical programming. For the solution of such a class of problems, we show the theory of vector optimization as a mathematical apparatus of acceptance of optimal solutions. Methods of solution of vector problems are directed to problem solving with equivalent criteria and with the given priority of a criterion. Following our research, the analysis and problem definition of decision making under the conditions of certainty and uncertainty are presented. We show the transformation of a mathematical model under the conditions of uncertainty into a model under the conditions of certainty. We present problems of acceptance of an optimal solution under the conditions of uncertainty with data that are represented by up to four parameters, and also show geometrical interpretation of results of the decision. Each numerical example includes input data (requirement specification) for modeling, transformation of a mathematical model under the conditions of uncertainty into a model under the conditions of certainty, making optimal decisions with equivalent criteria (solving a numerical model), and, making an optimal decision with a given priority criterion.

scholarly journals The Optimization Model of Earthquake Emergency Supplies Collecting with the Limited Period and Double-Level Multihub

2016 ◽  
Vol 2016 ◽  
pp. 1-12 ◽  
Author(s):  
Huang Xing
Keyword(s):  
Decision Making ◽  
Programming Model ◽  
Algorithm Design ◽  
Optimal Solution ◽  
Solution Space ◽  
Pso Algorithm ◽  
Optimal Decision ◽  
Interval Numbers ◽  
Collection Time ◽  
Emergency Supply

This paper constructed a multiobjective programming model and designed Particle Swarm Optimization (PSO) algorithm for earthquake emergency to solve the optimal decision-making question of Multihub emergency supplies collection network with constrained demand period and collection time as fuzzy interval numbers and capacity limit to hub nodes. As for algorithm design, a two-stage parallel solution mode was employed to achieve the global optimal solution in the solution space. At first, the paper is based on the constraint to the total time of emergency supplies collection system and the capacity limited to Multihub; this paper allocated the emergency supplies at each demand point to Multihub from which the emergency supply would be transferred. Secondly, this paper searched for the optimal plans from some feasible plans to determine the distribution directions and emergency supplies collection amount at emergency supplies provision points as well as the optimal collection cost that meet the constraint of demand time. Finally, the result of case verification showed that, compared with simulated annealing (SA) and sequential enumeration method (SEM), Multihub emergency supply collection model based on PSO parallel algorithm made a great improvement in the number of iterations and the optimal collection time, indicating that this model is feasible and effective and can be used in decision-making for earthquake emergency supply collection.

scholarly journals Optimal Battery Dispatch Using Finite-Input Set Non-Linear Model Predictive Control: Algorithm Development and Case Study

Electronics ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. 101
Author(s):  
Fathi Abugchem ◽  
Michael Short ◽  
Chris Ogwumike ◽  
Huda Dawood
Keyword(s):  
Decision Making ◽  
Energy Storage ◽  
Model Predictive Control ◽  
Linear Model ◽  
Predictive Control ◽  
Storage System ◽  
Cost Effective ◽  
Energy Storage System ◽  
Optimal Decision ◽  
Non Linear

The advancement in battery manufacturing has played a significant role in the use of batteries as a cost-effective energy storage system. This paper proposes an optimal charging and discharging strategy for the battery energy storage system deployed for economic dispatch and supply/demand balancing services in the presence of intermittent renewables such as solar photovoltaic systems. A decision-making strategy for battery charge/discharge operations in a discrete-time rolling framework is developed as a finite-input set of non-linear model predictive control instances and a dynamic programming procedure is proposed for its real-time implementation. The proposed scheme is tested on controllable loads and photovoltaic generation scenario in the premises of a sports centre, as a part of a pilot demonstration of the inteGRIDy EU-funded project. The test results confirm that the implemented stacking of the battery and optimal decision-making algorithm can enhance net saving in the electricity bill of the sports centre, and lead to corresponding CO2 reductions.

scholarly journals Optimal Troubleshooting for Electro-Mechanical Systems

2003 ◽  
Author(s):  
Robert Paasch ◽  
Parthsarathy Durgi
Keyword(s):  
Decision Making ◽  
Bayesian Networks ◽  
Approximate Method ◽  
Ad Hoc ◽  
Electromechanical System ◽  
Optimal Decision ◽  
Behavioral Models ◽  
Maintenance Costs ◽  
Standard Methods ◽  
Decision Sequence

When a complex electromechanical system fails, the troubleshooting procedure adopted is often complex and tedious. No standard methods currently exist to optimize the sequence of steps in a troubleshooting process. The ad hoc methods generally followed are less than optimal methods and can result in high maintenance costs. This paper describes the use of behavioral models and multistage decision-making models in Bayesian networks for representing the troubleshooting process. It discusses advantages in using these methods and the difficulties in implementing them. An approximate method to obtain optimal decision sequence for a troubleshooting process on a complex electromechanical system is also described.

Overview of the Hospital Formulary Systems in Hong Kong: Princess Margaret Hospital as a Baseline

1997 ◽  
Vol 31 (12) ◽  
pp. 1526-1531 ◽  
Author(s):  
Sophie Chang ◽  
Joyee WS Wong ◽  
Chloe WY Wong ◽  
Harry CC Chiu ◽  
Kenneth Raymond
Keyword(s):  
Decision Making ◽  
Hong Kong ◽  
Drug Evaluation ◽  
Cost Savings ◽  
Cost Effective ◽  
Formulary System ◽  
Formulary Decision ◽  
Princess Margaret Hospital ◽  
The Us ◽  
Hospital Pharmacies

OBJECTIVE: To investigate the popularity of formulary systems in all Hong Kong hospitals and to compare these with the newly introduced formulary system in a major government hospital, the Princess Margaret Hospital (PMH), as the baseline. DESIGN: Questionnaire and selected interviews by pharmacy students. SETTING: All hospital pharmacies in Hong Kong. PARTICIPANTS: Department managers (directors of pharmacy services) of hospital pharmacies. MAIN OUTCOME MEASURE: The popularity of the hospitals' formulary systems and their formulary decision-making strategies. Calculations of cost savings of the new formulary system in PMH and a comparison of the PMH system with the US standards were also made. RESULTS: Among 38 responding hospitals, 35 (92%) had a formulary handbook and 21 (55.3%) claimed to have a formulary system. The evaluation processes and formulary decision-making procedures were found to be inadequate because basic components in drug evaluation (e.g., standardized criteria for drug evaluation) were not used regularly. However, the formulary system in PMH was found to be comparable with the US standards. Substantial cost savings were made through rejection of less cost-effective drugs by the Formulary Subcommittee in PMH. CONCLUSIONS: In general, comprehensive formulary systems are still not popular in Hong Kong. This may be due to insufficient staffing and lack of administrative and physicians' support. The new formulary system in PMH can be used as a model to develop a successful formulary system in which hospital pharmacists can prove their expertise for the benefit of both hospitals and patients in Hong Kong.

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