RFID Based Smart Car Parking System Using IOT

Now a days the use of vehicles is increasing day by day, the major problem in densely populated areas is lack of parking availability. The RFID technique is the mostly used technique to overcome or eradicate the cause. The existing technique of RFID concept is to check the balance amount in the card rather than finding the availability of parking lots at remote location. The major disadvantage in this existing methodology is tracing the amount deducted and it varies from time to time on various slots. Hence we provide a solution i.e., by this proposed method we ensure an efficient monitoring system that allows for tracking availability of spaces in parking areas in remote areas like malls, parks and other public places as well. This project forecasts all the possible ways to reduce parking tension. This project aims at interfacing RFID concept with Internet of Things (IoT). IoT establishes a client server communication that enables the user for remote communication regarding availability of parking slots from distance. In order to enhance a mobile friendly environment an website is being developed that gives prior information to the user about the availability of parking slot and thereby enabling them to book the slot for parking from a distance and the slot remains booked for a period of half an hour there by waits for the user to arrive until the specified time is reached. When the time exceeds, the user needs to book the slot again if available. This ensures minimization of traffic constraints in parking areas. This can be implemented in shopping malls where usually traffic problems arise due to lack or unavailability of parking

Nonconvex piecewise linear knapsack problems

This paper considers the minimization version of a class of nonconvex knapsack problems with piecewise linear cost structure. The items to be included in the knapsack have a divisible quantity and a cost function. An item can be included partially in the given quantity range and the cost is a nonconvex piecewise linear function of quantity. Given a demand, the optimization problem is to choose an optimal quantity for each item such that the demand is satisfied and the total cost is minimized. This problem and its close variants are encountered in manufacturing planning, supply chain design, volume discount procurement auctions, and many other contemporary applications. Two separate mixed integer linear programming formulations of this problem are proposed and are compared with existing formulations. Motivated by different scenarios in which the problem is useful, the following algorithms are developed: (1) a fast polynomial time, near-optimal heuristic using convex envelopes; (2) exact pseudo-polynomial time dynamic programming algorithms; (3) a 2-approximation algorithm; and (4) a fully polynomial time approximation scheme. A comprehensive test suite is developed to generate representative problem instances with different characteristics. Extensive computational experiments show that the proposed formulations and algorithms are faster than the existing techniques

Multiattribute electronic procurement using goal programming

One of the key challenges of current day electronic procurement systems is to enable procurement decisions transcend beyond a single attribute such as cost. Consequently, multiattribute procurement have emerged as an important research direction. In this paper, we develop a multiattribute e-procurement system for procuring large volume of a single item. Our system is motivated by an industrial procurement scenario for procuring raw material. The procurement scenario demands multiattribute bids, volume discount cost functions, inclusion of business constraints, and consideration of multiple criteria in bid evaluation. We develop a generic framework for an e-procurement system that meets the above requirements. The bid evaluation problem is formulated as a mixed linear integer multiple criteria optimization problem and goal programming is used as the solution technique. We present a case study for which we illustrate the proposed approach and a heuristic is proposed to handle the computational complexity arising out of the cost functions used in the bids

Analyses for Service Interaction Networks with applications to Service Delivery

One of the distinguishing features of the services industry is the high emphasis on people interacting with other people and serving customers rather than transforming physical goods like in the traditional manufacturing processes. It is evident that analysis of such interactions is an essential aspect of designing effective and efficient services delivery. In this work we focus on learning individual and team behavior of different people or agents of a service organization by studying the patterns and outcomes of historical interactions. For each past interaction, we assume that only the list of participants and an outcome indicating the overall effectiveness of the interaction are known. Note that this offers limited information on the mutual (pairwise) compatibility of different participants. We develop the notion of service interaction networks which is an abstraction of the historical data and allows one to cast practical problems in a formal setting. We identify the unique characteristics of analyzing service interaction networks when compared to traditional analyses considered in social network analysis and establish a need for new modeling and algorithmic techniques for such networks. On the algorithmic front, we develop new algorithms to infer attributes of agents individually and in team settings. Our first algorithm is based on a novel modification to the eigen-vector based centrality for ranking the agents and the second algorithm is an iterative update technique that can be applied for subsets of agents as well. One of the challenges of conducting research in this setting is the sensitive and proprietary nature of the data. Therefore, there is a need for a realistic simulator for studying service interaction networks. We present the initial version of our simulator that is geared to capture several characteristics of service interaction networks that arise in real-life

Price and service competition with maintenance service bundling

In many equipment manufacturing industries, firms compete with each other not only on products price, but also on maintenance service. More and more traditional products oriented firms are offering their customers products bundled with maintenance service (P&S bundles). In this study, we examine firms’ incentive to offer customers products bundling with long-term maintenance or repair support service in a duopoly competitive environment. When providing P&S bundles, a firm need to determine the service level (in terms of average response time guarantee for the service in this paper) to offer and needs to build a service facility to handle the maintenance service requirements. Based on the analysis of three sub-game models, we characterize the market conditions in which only one firm, both firms or neither firm will offer P&S bundles. Finally, we analyze the affects of several market factors on firms’ strategy choices

Snakebite and its socio-economic impact on the rural population of Tamil Nadu, India

BACKGROUND: Snakebite represents a significant health issue worldwide, affecting several million people each year with as many as 95,000 deaths. India is considered to be the country most affected, but much remains unknown about snakebite incidence in this country, its socio-economic impact and how snakebite management could be improved. METHODS/PRINCIPAL FINDINGS: We conducted a study within rural villages in Tamil Nadu, India, which combines a household survey (28,494 people) of snakebite incidence with a more detailed survey of victims in order to understand the health and socio-economic effects of the bite, the treatments obtained and their views about future improvements. Our survey suggests that snakebite incidence is higher than previously reported. 3.9% of those surveyed had suffered from snakebite and the number of deaths corresponds to 0.45% of the population. The socio-economic impact of this is very considerable in terms of the treatment costs and the long-term effects on the health and ability of survivors to work. To reduce this, the victims recommended improvements to the accessibility and affordability of antivenom treatment. CONCLUSIONS: Snakebite has a considerable and disproportionate impact on rural populations, particularly in South Asia. This study provides an incentive for researchers and the public to work together to reduce the incidence and improve the outcomes for snake bite victims and their families

Benders-based winner determination algorithm for volume discount procurement auctions

This paper considers an industrial procurement of large volume of a single good, such as a raw material or a subcomponent. The procurement is implemented using volume discount auctions, in which the bids are nonconvex piecewise linear cost functions. The winner determination problem faced by the buyer is an NP-hard nonlinear knapsack problem. We propose a mixed integer linear formulation for the problem which has the following primal structure: if the integer variables are fixed at some feasible values, then solving the remaining linear variables is a continuous knapsack problem. Exploiting this feature, Benders' decomposition algorithm is developed and various techniques are proposed to accelerate the convergence of the algorithm. Experimental results for the random test data show the efficacy of the accelerating technique

Orchestrating a network of activities in the value chain

The orchestrator is a management literature metaphor to describe the role of a player who organizes and manages a set of activities in a network, by ensuring value creation opportunities in the system and value appropriation mechanisms for each player. In this paper, we consider orchestrators who do not own capacities but have access to a large pool of globally dispersed service providers in the various stages of the supply chain. For a given customer order, the orchestrator identifies the right set of service providers and coordinates the entire execution such that order is delivered as per the requirements. We propose a mixed integer program to optimally choose the service providers taking into account the capacities, production and distribution costs, international taxation, tariffs, and coordination costs

e-Procurement using goal programming

e-Procurement is an Internet-based business process for obtaining materials and services and managing their inflow into the organization. In this paper we develop multiattribute e-Procurement systems with configurable bids and formulate the bid evaluation problem as a linear integer multiple criteria optimization problem. Configurable bids allow multiple values for each attribute and for each value the bidder can specify price as a piecewise linear function of quantity. The suppliers can express volume discount bargaining strategy and economies of scale, using the above price function. The buyer can include several business rules and purchasing policies as side constraints in the optimization problem to evaluate the winning bids. We propose the use of goal programming techniques to solve the bid evaluation problem