Competitive analysis of online inventory problem with interrelated prices

This paper investigates the online inventory problem with interrelated prices in which a decision of when and how much to replenish must be made in an online fashion even without concrete knowledge of future prices. Four new online models with different price corre- lations are proposed in this paper, which are the linear-decrease model, the log-decrease model, the logarithmic model and the exponential model. For the first two models, the online algo- rithms are developed, and as the performance measure of online algorithm, the upper and lower bounds of competitive ratios of the algorithms are derived respectively. For the exponential and logarithmic models, the online algorithms are proposed by the solution of linear programming and the corresponding competitive ratios are analyzed, respectively. Additionally, the algorithm designed for the exponential model is optimal, and the algorithm for the logarithmic model is optimal only under some certain conditions. Moreover, some numerical examples illustrate that the algorithms based on the dprice-conservative strategy are more suitable when the purchase price fluctuates relatively flat.

Sentiment Analysis in Social Media for Competitive Environment Using Content Analysis

Education sector has witnessed several changes in the recent past.These changes have forced private universities into fierce competition with each other to get more students enrolled.This competition has resulted in the adoption of marketing practices by private universities similar to commercial brands.To get competitive gain,universities must observe and examine the students’feedback on their own social media sites along with the social media sites of their competitors.This study presents a novel framework which integrates numerous analytical approaches including statistical analysis,sentiment analysis,and text mining to accomplish a competitive analysis of social media sites of the universities.These techniques enable local universities to utilize social media for the identification of the most-discussed topics by students as well as based on the most unfavorable comments received,major areas for improvement.A comprehensive case study was conducted utilizing the proposed framework for competitive analysis of few top ranked international universities as well as local private universities in Lahore Pakistan.Experimental results show that diversity of shared content,frequency of posts,and schedule of updates,are the key areas for improvement for the local universities.Based on the competitive intelligence gained several recommendations are included in this paper that would enable local universities generally and Riphah international university(RIU)Lahore specifically to promote their brand and increase their attractiveness for potential students using social media and launch successful marketing campaigns targeting a large number of audiences at significantly reduced cost resulting in an increased number of enrolments.

Competitive analysis of price online inventory problem with cost function

In this paper,a new price is given to the online decision maker at the beginning of each day.The trader must decide how many items to purchase according to the current price.We present three variants and an online algorithm based on cost function.The competitive ratio of the online algorithm is given for each variant,which is a performance measure of an online algorithm.More importantly,we show that the online algorithm is optimal.

The Analysis of Competitiveness of China's Textiles and Clothing

This essay,starting with the development of the textile trade in China,analyzed the competitiveness of China's textiles and clothing industry,by means of two indexes:international market share and competitiveness index,combining with the factors of influencing the trade of China's textiles,finally got the conclusion.

An efficient and impartial online algorithm for kidney assignment network

An online algorithm balancing the efficiency and equity principles is proposed for the kidney resource assignment when only the current patient and resource information is known to the assignment network. In the algorithm, the assignment is made according to the priority, which is calculated according to the efficiency principle and the equity principle. The efficiency principle is concerned with the post-transplantation immunity spending caused by the possible post-operation immunity rejection and patient’s mental depression due to the HLA mismatch. The equity principle is concerned with three other factors, namely the treatment spending incurred starting from the day of registering with the kidney assignment network, the post-operation immunity spending and the negative effects of waiting for kidney resources on the clinical efficiency. The competitive analysis conducted through computer simulation indicates that the efficiency competitive ratio is between 6.29 and 10.43 and the equity competitive ratio is between 1.31 and 5.21, demonstrating that the online algorithm is of great significance in application.

Online scheduling of two type parallel jobs on identical machines

In this paper we consider an online scheduling of parallel jobs with preemption on identical machines, where jobs arrive over time. The objective is to minimize the makespan. For the problem that jobs have only two possible widths mj = 1 or m, we present an optimal online algorithm by using ＂temporary schedule＂.

An Online Algorithm Based on Replication for Using Spot Instances in IaaS Clouds

Infrastructure-as-a-Service(IaaS)cloud platforms offer resources with diverse buying options.Users can run an instance on the on-demand market which is stable but expensive or on the spot market with a significant discount.However,users have to carefully weigh the low cost of spot instances against their poor availability.Spot instances will be revoked when the revocation event occurs.Thus,an important problem that an IaaS user faces now is how to use spot in-stances in a cost-effective and low-risk way.Based on the replication-based fault tolerance mechanism,we propose an on-line termination algorithm that optimizes the cost of using spot instances while ensuring operational stability.We prove that in most cases,the cost of our proposed online algorithm will not exceed twice the minimum cost of the optimal of-fline algorithm that knows the exact future a priori.Through a large number of experiments,we verify that our algorithm in most cases has a competitive ratio of no more than 2,and in other cases it can also reach the guaranteed competitive ratio.

Competitive Analysis of Two Special Online Device Replacement Problems

When a new investment opportunity of purchasing a new device occurs, the investors must decide whether or not and when to buy this device in an online fashion. That is, the online player must make an investment decision while neither future demand for orders nor future investment opportunities are known. This problem which generalizes the basic leasing problem has been introduced by Azar et al., and then two special cases have been studied by Damaschke. In the so-called equal prices model a 2-competitive algorithm is devised and a 1.618 lower bound is given. Here we make use of an averaging technique and obtain a better tight lower bound of 2, in other words, this lower bound cannot be improved. Furthermore, another special case which only considers two-stage device replacement is studied in this paper. Accounting for the interest rate is an essential feature of any reasonable financial model. Therefore, we explore the two-stage model with and without the interest rate respectively. In addition, we introduce the risk-reward model to analyze this problem and improve the competitive ratio performance.

Qualitative Analysis of a Class of Competitive and Cooperative Systems

Hirsch[1,2] studied the limiting behavior of solutions of competitive or cooperative systems, and showed that ifL is an ω-limit set of a three-dimensional cooperative system, which contains no equilibrium, thenL is a nonattracting closed orbit. Smith[3] considered a three-dimensional irreducible competitive system and showed that an ω-limit set containing no equilibrium must be a closed orbit which has a simple Floquet multiplier λ<1, and may be attracting. In this paper we carry out the qualitative analysis of a class of competitive and cooperative systems, and a generalization of the result of Levine[4] is given. The stability problem of closed orbits raised in [5] and [6] is resolved.

Preemptive Semi-online Algorithms for Parallel Machine Scheduling with Known Total Size

This paper investigates preemptive semi-online scheduling problems on m identical parallel machines, where the total size of all jobs is known in advance. The goal is to minimize the maximum machine completion time or maximize the minimum machine completion time. For the first objective, we present an optimal semi-online algorithm with competitive ratio 1. For the second objective, we show that the competitive ratio of any semi-online algorithm is at least （2m-3）/（m-1） for any m〉2 and present optimal semi-online algorithms for m = 2, 3.

Three Open On- line CombinatorialOptimization Problems

：We present three open combinatorial optimization problems from the standpoint of competitive analysis, in the case that there is no complete information.

Two Online Algorithms for the Ambulance Systems

An ambulance system consists of a collection S = {s1,...,sm ) sm} of emergency centers in a metric space M. Each emergency center si has a positive integral capacity ci to denote, for example, the number of ambulances at the center. There are n = =1, ci patients requiring ambulances at different times tj and every patient is associated with a number bj, the longest time during which the patient can wait for ambulance. An online algorithm A will decide which emergency center sends an ambulance to serve a request for ambulance from a patient at some time. If algorithm A sends an ambulance in si to serve a patient rj, then it must be observed that di,j/v < bj, where di,j is the distance between emergency center si and patient rj, and v is the velocity of ambulance. A fault of algorithm A is such that to a request for ambulance at some time tj with j ≤n, for every i with di,j/v < bj, there is no ambulance available in si. The cost of an algorithm A is the number of faults A makes. This paper gives two algorithms B and C, where B is the local greedy algorithm and C is a variant of balancing costs, and proves that both B and C have no bounded competitive ratios. Moreover, given any sequence a of requests for ambulances without optimal faults, the cost of C on σis less than or equal to [n/3] and that of B is less than or equal to [n/2].

An Intelligent Energy Management System for Large-Scale Charging of Electric Vehicles

The problem of large-scale charging of electric vehicles(EVs)with consumer-imposed charging deadlines is considered.An architecture for the intelligent energy management system(iEMS)is introduced.The iEMS consists of an admission control and pricing module,a scheduling module that determines the charging sequence,and a power dispatch module that draws power from a mix of storage,local renewable energy sources,and purchased power from the grid.A threshold admission and greedy scheduling(TAGS)policy is proposed to maximize operation profit.The performance of TAGS is analyzed and evaluated based on average and worst-case performance measures and the optimality of TAGS is established for some instances.Numerical simulations demonstrate that TAGS achieves noticeable performance gains over benchmark techniques.