scholarly journals No Magic for Market Entry in the Field: Evidence from Taxi Markets

2021 ◽  
Author(s):  
Xiaoyu Xia ◽  
Juin Kuan Chong
Keyword(s):  
Dynamic Programming ◽  
Market Entry ◽  
Optimal Solution ◽  
Strategic Thinking ◽  
Model Fit ◽  
Market Knowledge ◽  
Taxi Drivers ◽  
Movement Data ◽  
Wage Rates ◽  
Field Evidence

We study taxi markets in Singapore to understand market entry in the field. Although market-entry games in the laboratory consistently produce equilibrium outcomes, we show that a lack of market knowledge hinders the markets from consistently reaching equilibrium in the field. In Singapore, a small, 720-square-kilometre island city that can be divided into 29 taxi markets, full equilibrium is elusive: 68% of the market-entry decisions made by the 2,728 taxi drivers in our data could be improved. Using three months of earnings and detailed movement data from these taxi drivers, we find an average 20% gap in marginal wage rates across markets. We use dynamic programming to derive the optimal solution for more than 3 million search decisions and find that only 32% of the searches ended in an optimal market. Finally, we find that market knowledge developed in a given month explains an additional 3% variation of the earning losses in the 2.6 million decisions for the subsequent two months, an improvement in model fit of 74%, whereas strategic thinking and minimization risk have no impact on earning loss. This paper was accepted by Yan Chen, behavioral economics and decision analysis.

scholarly journals One task of routing jobs in high radiation conditions

2021 ◽  
Vol 58 ◽  
pp. 94-126
Author(s):  
A.G. Chentsov ◽  
A.A. Chentsov ◽  
A.N. Sesekin
Keyword(s):  
Dynamic Programming ◽  
Numerical Solution ◽  
Model Problem ◽  
Optimal Solution ◽  
High Radiation ◽  
Dose Load ◽  
Route Problem ◽  
Precedence Conditions ◽  
Sequential Bypass ◽  
Radiation Conditions

The problem of sequential bypass of megalopolises is investigated, focused on the problem of dismantling a system of radiation hazardous objects under constraints in the form of precedence conditions. The radiation impact on the performers is assessed by the doses received during movements and during the performance of dismantling works. The route problem of minimizing the dose load of workers carrying out dismantling in one or another sequence of operations is considered. The procedure for constructing an optimal solution using a variant of dynamic programming is investigated. On this basis, an algorithm is built, implemented on a PC. Examples of the numerical solution of a model problem for the minimum dose load are given.

scholarly journals THE OPTIMAL PRINCIPLE OF BELLMAN IN THE PROBLEM OF OPTIMAL MEANS DISTRIBUTION BETWEEN ENTERPRISES FOR THE EXPANSION OF PRODUCTION

2019 ◽  
pp. 132-138 ◽  
Author(s):  
A. Tarasenko ◽  
I. Egorova
Keyword(s):  
Dynamic Programming ◽  
Nonlinear Programming ◽  
Optimal Solution ◽  
Optimal Distribution ◽  
Optimality Principle ◽  
Numerical Example ◽  
Maximum Profit ◽  
Cost Forecasting ◽  
Method Of Dynamic Programming ◽  
Minimum Costs

The method of dynamic programming has been considered, which is used in solving multiple problems in economics, on the example of using Bellman’s optimality principle for solving nonlinear programming problems. On a specific numerical example, the features of the solution have been shown in detail with all the calculations. The problem of optimal distribution of funds among enterprises for the expansion of production has been formulated, which would give the maximum total increase in output. The solution of the task has been presented in the case, when the number of enterprises is 3. It has been shown, that the Bellman optimality principle allows you solve applied problems of cost forecasting with obtaining the optimal solution-maximum profit at minimum costs.

An Optimal Power Management Strategy for Hydraulic Hybrid Output Coupled Power-Split Transmission

2009 ◽  
Author(s):  
Rajneesh Kumar ◽  
Monika Ivantysynova
Keyword(s):  
Dynamic Programming ◽  
Power Management ◽  
Control Strategy ◽  
Management Strategy ◽  
Optimal Solution ◽  
Programming Approach ◽  
Power Management Strategy ◽  
Optimal Power ◽  
Power Split ◽  
Instantaneous Optimization

Power-split drive represents a class of Continuously Variable Transmission (CVT) that combines the convenience of CVT with the high overall transmission efficiency. In its hybrid configuration, a high pressure accumulator is used to capture the braking energy that is regenerated to aid the engine power during the next propulsion event. Output coupled power split drives are particularly suited for small and medium duty vehicle applications. In this work, optimal power management strategy has been designed based on Dynamic Programming approach. Although the control strategy obtained by Dynamic Programming is non-causal, it represents the benchmark solution against which other implementable power management schemes can be compared. Another control strategy based on instantaneous optimization is also discussed where a given cost function is minimized at every instant. It results in a sub-optimal solution that is practical and implementable. Finally, Dynamic Programming results are utilized to discuss the possible improvements that can be made to the instantaneous optimization based control strategy.

REAL OPTIONS: BATCH PROCESS AND MARKET ENTRY/EXIT DECISIONS UNDER UNCERTAINTY

2004 ◽  
Vol 21 (01) ◽  
pp. 35-52 ◽  
Author(s):  
CHIN-TSAI LIN ◽  
CHENG-RU WU
Keyword(s):  
Dynamic Programming ◽  
Exchange Rate ◽  
Stochastic Optimization ◽  
Control Problem ◽  
Real Options ◽  
Market Entry ◽  
Rational Expectations ◽  
Batch Process ◽  
Production Model ◽  
Optimization Control

Under uncertainty of exchange rate, we extend the batch process production model of Lin et al. (2002) by considering an export-oriented manufacturer making decisions to switch freely between domestic and foreign locations. The export-oriented manufacturer is risk neutral and has rational expectations. We use dynamic programming and Lagrange multiplies for a stochastic optimization control problem to get the productive value of exporter produces in domestic and foreign locations. Next, the export-oriented manufacturer can make decision regarding the optimal entry (exit) trigger for transferable locations wherever the product locations are. It provides the supplier with another way to make decisions.

Optimization of Fuel Economy of Hybrid Electric Vehicles Using Set Based Dynamic Programming

2014 ◽  
Author(s):  
Nikhil Ramaswamy ◽  
Nader Sadegh
Keyword(s):  
Dynamic Programming ◽  
Fuel Economy ◽  
Hybrid Electric Vehicle ◽  
Optimal Solution ◽  
The State ◽  
State Variables ◽  
Discrete Time System ◽  
Real Time Control ◽  
Time Step ◽  
Hybrid Electric

Dynamic Programming (DP) technique is an effective algorithm to find the global optimum. However when applying DP for finite state problems, if the state variables are discretized, it increases the cumulative errors and leads to suboptimal results. In this paper we develop and present a new DP algorithm that overcomes the above problem by eliminating the need to discretize the state space by the use of sets. We show that the proposed DP leads to a globally optimal solution for a discrete time system by minimizing a cost function at each time step. To show the efficacy of the proposed DP, we apply it to optimize the fuel economy of the series and parallel Hybrid Electric Vehicle (HEV) architectures and the case study of Chevrolet Volt 2012 and the Honda Civic 2012 for the series and parallel HEV’s respectively are considered. Simulations are performed over predefined drive cycles and the results of the proposed DP are compared to previous DP algorithm (DPdis). The proposed DP showed an average improvement of 2.45% and 21.29% over the DPdis algorithm for the series and the parallel HEV case respectively over the drive cycles considered. We also propose a real time control strategy (RTCS) for online implementation based on the concept of Preview Control. The RTCS proposed is applied for the series and parallel HEV’s over the drive cycles and the results obtained are discussed.

scholarly journals A Hybrid Dynamic Programming for Solving Fixed Cost Transportation with Discounted Mechanism

2016 ◽  
Vol 2016 ◽  
pp. 1-9
Author(s):  
Farhad Ghassemi Tari
Keyword(s):  
Dynamic Programming ◽  
Programming Model ◽  
Transportation Network ◽  
Dynamic Programming Algorithm ◽  
Optimal Solution ◽  
Transportation Cost ◽  
Solution Algorithm ◽  
Transportation Costs ◽  
Programming Algorithm ◽  
Fixed Cost

The problem of allocating different types of vehicles for transporting a set of products from a manufacturer to its depots/cross docks, in an existing transportation network, to minimize the total transportation costs, is considered. The distribution network involves a heterogeneous fleet of vehicles, with a variable transportation cost and a fixed cost in which a discount mechanism is applied on the fixed part of the transportation costs. It is assumed that the number of available vehicles is limited for some types. A mathematical programming model in the form of the discrete nonlinear optimization model is proposed. A hybrid dynamic programming algorithm is developed for finding the optimal solution. To increase the computational efficiency of the solution algorithm, several concepts and routines, such as the imbedded state routine, surrogate constraint concept, and bounding schemes, are incorporated in the dynamic programming algorithm. A real world case problem is selected and solved by the proposed solution algorithm, and the optimal solution is obtained.

A dynamic programming solution of financial rotation ages for coppicing tree species

1986 ◽  
Vol 16 (4) ◽  
pp. 799-801 ◽  
Author(s):  
David E. Tait
Keyword(s):  
Dynamic Programming ◽  
Tree Species ◽  
Optimal Solution ◽  
Eucalyptus Plantation ◽  
Programming Solution ◽  
Dynamic Programming Solution

The optimal solution to the coppice problem, the problem of when to cut and when to replant a coppice, is shown to satisfy a simple recursive relationship. This recursive relationship is solved using dynamic programming. The approach is illustrated using an example of a eucalyptus plantation.

scholarly journals Comparison of Dynamic Programming Algorithm and Greedy Algorithm on Integer Knapsack Problem in Freight Transportation

2018 ◽  
Vol 5 (1) ◽  
pp. 49 ◽  
Author(s):  
Global Ilham Sampurno ◽  
Endang Sugiharti ◽  
Alamsyah Alamsyah
Keyword(s):  
Dynamic Programming ◽  
Greedy Algorithm ◽  
Knapsack Problem ◽  
Dynamic Programming Algorithm ◽  
Optimal Solution ◽  
Freight Transportation ◽  
Total Weight ◽  
Knapsack Problems ◽  
Programming Algorithm ◽  
Selection Of

At this time the delivery of goods to be familiar because the use of delivery of goods services greatly facilitate customers. PT Post Indonesia is one of the delivery of goods. On the delivery of goods, we often encounter the selection of goods which entered first into the transportation and  held from the delivery. At the time of the selection, there are Knapsack problems that require optimal selection of solutions. Knapsack is a place used as a means of storing or inserting an object. The purpose of this research is to know how to get optimal solution result in solving Integer Knapsack problem on freight transportation by using Dynamic Programming Algorithm and Greedy Algorithm at PT Post Indonesia Semarang. This also knowing the results of the implementation of Greedy Algorithm with Dynamic Programming Algorithm on Integer Knapsack problems on the selection of goods transport in PT Post Indonesia Semarang by applying on the mobile application. The results of this research are made from the results obtained by the Dynamic Programming Algorithm with total weight 5022 kg in 7 days. While the calculation result obtained by Greedy Algorithm, that is total weight of delivery equal to 4496 kg in 7 days. It can be concluded that the calculation results obtained by Dynamic Programming Algorithm in 7 days has a total weight of 526 kg is greater when compared with Greedy Algorithm.

scholarly journals A New Approach to Find an Optimal Solution of a Fuzzy Linear Programming Problem by Fuzzy Dynamic Programming

2018 ◽  
Vol 7 (4.10) ◽  
pp. 360
Author(s):  
T. Nagalakshmi ◽  
G. Uthra
Keyword(s):  
Dynamic Programming ◽  
Linear Programming ◽  
Objective Function ◽  
Programming Problem ◽  
Linear Programming Problem ◽  
Optimal Solution ◽  
Fuzzy Linear Programming ◽  
New Approach ◽  
The Cost ◽  
Recursive Equations

This paper mainly focuses on a new approach to find an optimal solution of a fuzzy linear programming problem with the help of Fuzzy Dynamic Programming. Linear programming deals with the optimization of a function of variables called an objective function, subject to a set of linear inequalities called constraints. The objective function may be maximizing the profit or minimizing the cost or any other measure of effectiveness subject to constraints imposed by supply, demand, storage capacity, etc., Moreover, it is known that fuzziness prevails in all fields. Hence, a general linear programming problem with fuzzy parameters is considered where the variables are taken as Triangular Fuzzy Numbers. The solution is obtained by the method of FDP by framing fuzzy forward and fuzzy backward recursive equations. It is observed that the solutions obtained by both the equations are the same. This approach is illustrated with a numerical example. This feature of the proposed approach eliminates the imprecision and fuzziness in LPP models. The application of Fuzzy set theory in the field of dynamic Programming is called Fuzzy Dynamic Programming. 

On the optimal control of stationary diffusion processes with inaccessible boundaries and no discounting

1971 ◽  
Vol 8 (03) ◽  
pp. 551-560 ◽  
Author(s):  
R. Morton
Keyword(s):  
Optimal Control ◽  
Dynamic Programming ◽  
Diffusion Processes ◽  
Necessary Conditions ◽  
Optimal Solution ◽  
Multidimensional Case ◽  
Potential Cost ◽  
One Dimensional ◽  
Dynamic Programming Equation ◽  
Stationary Diffusion

Summary Because there are no boundary conditions, extra properties are required in order to identify the correct potential cost function. A solution of the Dynamic Programming equation for one-dimensional processes leads to an optimal solution within a wide class of alternatives (Theorem 1), and is completely optimal if certain conditions are satisfied (Theorem 2). Necessary conditions are also given. Several examples are solved, and some extension to the multidimensional case is shown.

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