EFFECTS OF TRADABLE BOTTLENECK PERMITS AND PARETO IMPROVEMENT UNDER USERS' HETEROGENEITY IN SCHEDULE FLEXIBILITY AND TOLL RESISTANCE

2016 ◽  
Vol 72 (5) ◽  
pp. I_607-I_616
Author(s):  
Katsuya SAKAI ◽  
Takahiko KUSAKABE ◽  
Yasuo ASAKURA
Keyword(s):  
Pareto Improvement ◽  
Schedule Flexibility

scholarly journals Impacts of Metering-Based Dynamic Priority Schemes

2021 ◽  
Author(s):  
Raphaël Lamotte ◽  
André de Palma ◽  
Nikolas Geroliminis
Keyword(s):  
Arrival Time ◽  
Cost Savings ◽  
Pareto Improvement ◽  
Modal Shift ◽  
Dynamic Priority ◽  
Schedule Flexibility ◽  
Set Up ◽  
Priority Schemes ◽  
Pareto Improving ◽  
Small Capacity

Several works published over the last two decades have shown for a stylized set-up with homogeneous users that metering-based priority (MBP) schemes may generate Pareto improving departure time adjustments similar to those induced by congestion pricing, but without any financial transaction. We investigate whether MBP (i) still generates significant savings and (ii) remains Pareto-improving, with various sources of heterogeneity (in schedule flexibility, desired arrival time, and capacity usage). We consider two types of schemes: one where the priority status is allocated randomly (R-MBP) and another (HOV-MBP), which only prioritizes users with small capacity usage (e.g., carpoolers). We find that the relative total cost savings of R-MBP decrease with heterogeneity in flexibility, but may increase with heterogeneity in desired arrival time. It fails however to be Pareto-improving, as nonprioritized users are almost systematically worse-off. HOV-MBP circumvents this issue by generating an ordering effect and a modal shift, which both contribute to a better distribution of benefits among users. Under favorable circumstances, they may even restore a Pareto improvement. Overall, MBP appears as a realistic way to alleviate congestion, scoring well both in terms of efficiency and social acceptability.

scholarly journals Search Acceleration of Evolutionary Multi-Objective Optimization Using an Estimated Convergence Point

Mathematics ◽  
2019 ◽  
Vol 7 (2) ◽  
pp. 129 ◽  
Author(s):  
Yan Pei ◽  
Jun Yu ◽  
Hideyuki Takagi
Keyword(s):  
Parameter Space ◽  
Statistical Tests ◽  
Distribution Characteristic ◽  
Multi Objective Optimization ◽  
Pareto Improvement ◽  
Pareto Solutions ◽  
Pareto Solution ◽  
Multi Objective ◽  
Objective Space ◽  
Convergence Point

We propose a method to accelerate evolutionary multi-objective optimization (EMO) search using an estimated convergence point. Pareto improvement from the last generation to the current generation supports information of promising Pareto solution areas in both an objective space and a parameter space. We use this information to construct a set of moving vectors and estimate a non-dominated Pareto point from these moving vectors. In this work, we attempt to use different methods for constructing moving vectors, and use the convergence point estimated by using the moving vectors to accelerate EMO search. From our evaluation results, we found that the landscape of Pareto improvement has a uni-modal distribution characteristic in an objective space, and has a multi-modal distribution characteristic in a parameter space. Our proposed method can enhance EMO search when the landscape of Pareto improvement has a uni-modal distribution characteristic in a parameter space, and by chance also does that when landscape of Pareto improvement has a multi-modal distribution characteristic in a parameter space. The proposed methods can not only obtain more Pareto solutions compared with the conventional non-dominant sorting genetic algorithm (NSGA)-II algorithm, but can also increase the diversity of Pareto solutions. This indicates that our proposed method can enhance the search capability of EMO in both Pareto dominance and solution diversity. We also found that the method of constructing moving vectors is a primary issue for the success of our proposed method. We analyze and discuss this method with several evaluation metrics and statistical tests. The proposed method has potential to enhance EMO embedding deterministic learning methods in stochastic optimization algorithms.

scholarly journals Conventional and Unconventional Monetary Policy with Endogenous Collateral Constraints

2015 ◽  
Vol 7 (1) ◽  
pp. 1-43 ◽  
Author(s):  
Aloísio Araújo ◽  
Susan Schommer ◽  
Michael Woodford
Keyword(s):  
Central Bank ◽  
Financial Constraints ◽  
Aggregate Demand ◽  
Pareto Improvement ◽  
Interest Rate Policy ◽  
Collateral Constraints ◽  
Additional Dimension ◽  
Rate Policy ◽  
Asset Purchases ◽  
The One

We consider the effects of central bank purchases of a risky asset as an additional dimension of policy alongside “conventional” interest rate policy in a general-equilibrium model of asset pricing with endogenous collateral constraints. The effects of asset purchases depend on the way that they affect collateral constraints. We show that under some circumstances, central bank purchases relax financial constraints, increase aggregate demand, and may even achieve a Pareto improvement; but in other cases, they tighten financial constraints, reduce aggregate demand, and lower welfare. The latter case is almost certainly the one that arises if central bank purchases are sufficiently large. (JEL D51, E43, E44, E52, E58)

scholarly journals Liquidity Choice and Misallocation of Credit

2019 ◽  
Vol 2019 (284) ◽  
Author(s):  
Ehsan Ebrahimy
Keyword(s):  
Interest Rate ◽  
Type I ◽  
Pareto Improvement ◽  
Government Bonds ◽  
High Interest Rate ◽  
Liquid Asset ◽  
Constrained Efficiency ◽  
Liquid Type ◽  
The Interest Rate

This paper studies a novel type of misallocation of credit between investments of varying liquidity. One type of investment is more liquid, i.e., its return is more pledgeable, and the other is more productive. Low liquidities of both investment types imply that the allocation of credit is constrained inefficient and that there is overinvestment in the liquid type. Constrained inefficient equilibria feature non-positive, i.e., one less than or equal the economy’s growth rate, and yet too high interest rate, too much investment and too little consumption. Financial development can reduce long-term welfare and output in a constrained inefficient equilibrium if it raises the liquidity of the liquid type. I show a maximum liquid asset ratio or a simple debt tax can achieve constrained efficiency. Introducing government bonds can make Pareto improvement whenever it does not raise the interest rate.

scholarly journals Pricing and Collection Rate for Remanufacturing Industry considering Capacity Constraint in Recycling Channels

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-13 ◽  
Author(s):  
Lang Xu ◽  
Jia Shi ◽  
Jihong Chen
Keyword(s):  
Supply Chain ◽  
Production Cost ◽  
Closed Loop ◽  
Capacity Constraint ◽  
Coordination Mechanism ◽  
Selling Price ◽  
Pareto Improvement ◽  
Competition Intensity ◽  
Closed Loop Supply Chain ◽  
Collection Rate

This paper explores the decision-making and coordination mechanism of pricing and collection rate in a closed-loop supply chain with capacity constraint in recycling channels, which consists of one manufacturer and one retailer. On the basis of game theory, the equilibriums of decisions and profits in the centralized and decentralized scenarios are obtained and compared. Through the performance analysis of a different scenario, a higher saving production cost and lower competition intensity trigger the members to engage in remanufacturing. Furthermore, we try to propose a two-part tariff contract through bargaining to coordinate supply chain and achieve a Pareto improvement. The results show that when the capacity constraints in recycling channels exceed a threshold, the decisions and profit will change. Additionally, for closed-loop supply chain, the selling price is more susceptible to the influence of capacity constraint in recycling channel than the members’ profit.

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