BACKGROUND

[0001] The present invention relates to cost computation systems. More particularly, the present invention relates to a system and method to compute an optimum cost for a specific activity based on several parameters.

[0002] In large or mid-size organizations, it is often required to provide or procure various types of services. These services may benefit the organization's customers, employees, vendors or other entities that are interacting with the organization. In order to facilitate better interaction, organizations use several business applications.

[0003] In recent years, many organizations have adopted Service Oriented Architecture (SOA) for building and integrating their business applications. Each service exposes a well-defined interface that is independent of the service's underlying implementation (e.g., hardware/software platform, programming language, etc.). Using these interfaces, the various services can interact to provide services to, and consume services from, each other.

[0004] However, in the current scenario, the workforce of an organization is mobile, remote and largely distributed. Such a structure often creates difficulties for an organization to provide optimum support and services to its employees. As a result, the a large amount of time and resources is spent on identifying, procuring, managing, coordinating and accessing the various services that are required for the organization.

[0005] For example, employees may be required to attend training programs that require travel plans including airfare, sleeping accommodation and local transportation. The distributed nature of the workforce could result in numerous people staying in varying hotels, renting individual cars and/or transportation to and from airports and event locations. This in turn, considerable increases the costs to the organization.

[0006] Therefore, there is a need for developing a system that identifies an optimized solution or a set of alternate solutions to help minimize objective functions such as cost, time, resources and the like.

BRIEF DESCRIPTION

[0007] Briefly, according to one aspect of the present technique, a system for computing an optimum solution for a service is provided. The system comprises one or more computing devices configured to enable a plurality of users to provide a plurality of input parameters to solicit one or more services. The system further includes a server system configured to communicate with the plurality of computing devices and configured to execute an optimization module, wherein the optimization module is configured to generate the optimum solution based on the plurality of input parameters and compute a lowest cost of the one or more services.

[0008] In another embodiment, a system for computing an optimum solution for training program. The system comprises one or more computing devices configured to enable a plurality of users to provide a plurality of input parameters for the training program. The system further includes a server system configured to communicate with the plurality of computing devices and configured to execute an optimization module, wherein the optimization module is configured to generate the optimum cost for the training program based on the plurality of input parameters.

DRAWINGS

[0001] These and other features, aspects, and advantages of the present invention will become better understood when the following detailed description is read with reference to the accompanying drawings in which like characters represent like parts throughout the drawings, wherein:

[0002] FIG. 1 illustrates one embodiment of a system for computing an optimum solution for multiple services according to aspects of the present technique;

[0003] FIG.2 is a flow chart illustrating one method for determining an optimum solution for a solicited service according to embodiments of the present invention;

[0004] FIG. 3 is a block diagram illustrating a manner in which on embodiment of an optimization module uses various parameters to generate a solution set;

[0005] FIG. 4 is a flow chart illustrating one technique by which an optimum training program is determined according to aspects of the present invention;

[0006] FIG. 5 to FIG. 12 illustrates several example screen shots of the user interface that is used by the optimization module according to several aspects of the present technique; and

[0007] FIG. 13 is a block diagram illustrating an example computing device 100 that is arranged for generating an optimum solution for a specific service.

DETAILED DESCRIPTION

[0008] As discussed in detail below, embodiments of the present technique function provide nanocomposites for use in applications such as drug delivery, therapy, etc. References in the specification to "one embodiment", "an embodiment", "an exemplary embodiment", indicate that the embodiment described may include a particular feature, structure, or characteristic, but every embodiment may not necessarily include the particular feature, structure, or characteristic. Moreover, such phrases are not necessarily referring to the same embodiment. Further, when a particular feature, structure, or characteristic is described in connection with an embodiment, it is submitted that it is within the knowledge of one skilled in the art to affect such feature, structure, or characteristic in connection with other embodiments whether or not explicitly described.

[0009] Turning now to drawings and referring first to FIG. 1 illustrates a system 10 suitable for practicing methods and systems consistent with the present invention. The system includes a server 12 that communicates with a plurality of computing devices or computers 16, 18 and 20 via a telecommunication network 14. The telecommunication network 14 may be a local area network, wide area network, or the Internet. Each block is described further detail below.

[0010] Methods consistent with the present invention provide an optimization module for computing costs for a range of services. Examples of services include medical tourism where the cost of total cost of the treatment can be optimized over the cost doctor, hospital, travel, stay, and the like. Another example would be during a family event such as a wedding where the total cost can be optimized over the preferential dates, availability of venue, travel and stay of all the attendees. Yet another example is the scheduling of conferences where the total cost can be optimized over the availability of venue, travel and stay of all the attendees. In general, a service can generally refer to an event that requires coordination between multiple participants located at different places and travelling to a single or multiple locations.

[0011] The optimization module 22 comprises a user interface that may be presented to a plurality of users via network 14. In one embodiment, the user interface 24 enables the user to select a specific service from a list of services. The user interface enables users to provide a plurality of parameters for the requested service.

[0012] In one embodiment, the user interface is presented to the users using computing device 16, 18 and 20 running a browser. Server 12 receives the input parameters and executes an optimization module to compute an optimum solution for the requested service. The manner in which the optimum solution is computed is described in further detail below.

[0013] FIG.2 is a flow chart illustrating one method for determining an optimum solution for a solicited service according to embodiments of the present invention. The technique described below outline the steps for determining an optimum solution for a requested service.

[0014] At step 32, input parameters are received from a plurality of users. In one embodiment, the input parameters include service parameters and infrastructure parameters. Examples of service parameters include the type of service being requested, date and time information, availability of users, location of the users, and the like. Examples of infrastructure parameters include logistics information such a venues, travel if required, accommodation of users and the like.

[0015]At step 34, the input parameters are prioritized. In one embodiment, the optimization module generates a priority value for each input parameter. In additional, new parameters may also be added by the optimization module based on the priorities of the input parameters. Using the input parameters along with their priorities, the optimization module generates solution set as shown in step 36.

[0016] At step 38, an optimum solution is selected from the solution set depending on the users' requirement. For example, if the users' requirement is to select a service based on a minimum cost, the solution with the lowest cost is considered the optimum solution. The manner in which the optimization module generates a solution set is described below in further detail.

[0017[ FIG- 3 is a block diagram illustrating a manner in which on embodiment of an optimization module uses various parameters to generate a solution set. The optimization module described herein may be implemented on a computing device, a server system, cloud based infrastructure and the like. The functioning of the optimization module is describe din further detail below.

[0018] The optimization module 42 receives input parameters 46 for a specific service. The input parameters are received from a plurality of users. User interface 44 enables users to provide the input parameters based on the requested service. In one embodiment, the user interface is a web based application that executes on a user's computing device.

[0019] The optimization module is further configured to obtain user data 48 from the user's computing device. User data typically includes calendar availability for selected dates, the user's profile data, and the like. The optimization module is also configured to retrieve or store user data in repository 50.

[0020] The optimization module is configured to generate a solution set 52 based on the input parameters received. In one embodiment, the optimization module generates the solution set 52 based on the input parameters and the user data. The solution set comprises several solutions for the requested service. Each solution is based upon a specific parameter such as cost, date, time, distance, etc. The optimum solution is selected based on the parameters that are most important to the user. For example, if the user requires a service at a minimum cost, the solution with lowest cost is selected as the optimum solution from the solution set.

[0021] As will be appreciated in one skilled in the art, the optimization module can be used to generate optimal solutions for a variety of services based upon several input parameters. An example of such a service is generating a training program for employees in an organization. The manner in which the optimization module determines an optimum training plan is described below with references to FIG. 4.

[0022] FIG. 4 is a flow chart illustrating one technique by which an optimum training program is determined according to aspects of the present invention. The process 60 implements an optimization module to arrive at the optimum training program. Each step in the process is described in further detail below.

[0023] At step 58, a training program request is received by an organization's training team. In the specific example, it is assumed that the participants of the training program are the employees of the organization. It is also assumed that the trainer or trainers being employed for the training program is an employee of the organization. In addition, for the purposes of this example only, the optimum solution corresponds to the solution that is of the lowest cost.

[0024] At step 58, the optimization module creates a training plan based on the training request that was received. The training plan is created based on the training request received. The optimization module may, for example, retrieve historic data with respect to similar training plans.

[0025] At step 62, the input parameters are prioritized. The optimization module is configured to retrieve trainers' availability and participants' availability from the respective calendars. Input parameters may be prioritized based on availability of the trainer and/or the participants as shown in step 64. For example, if the trainer is not available for a certain date, the optimization module may be configured to select a next available date. Similarly, the optimization module is configured to select a date that will ensure maximum participation. Thus, each input parameter is selected based on availability of trainer and participants as shown in step 66.

[0026] At step 68, an optimum training program is determined. As the optimum training program for this example is based on the lowest cost, the optimization module computes a cost breakdown for a set of training programs. The cost breakdown comprises the cost of a trainer for a particular date, a travel cost for the trainer and participants based on a mode of transport, a location, a date and the total number of people travelling, among other things. While generating the cost, the optimization module may also include lodging costs which is usually a function of the lodging facility, a location, a number of days that are request, and the like. In addition, the optimization module also accounts for a venue cost.

[0027] FIG. 5 to FIG. 12 illustrates several example screen shots of the user interface that is used by the optimization module according to several aspects of the present technique. FIG. 5 illustrates screen 70 that is used to gather trainer information. FIG. 6 illustrates screen 72 that is implemented to receive participant information. FIG. 7 illustrates screen 74 that is implemented to receive venue information. FIG. 8 illustrates screen 76 that is implemented to receive travel related information. FIG. 9 illustrates screen 78 that is implemented to display various flight options between two locations to a participant/trainer. FIG. 10 illustrates screen 80 that is implemented to receive information regarding a various costs for a several commercial airliners. FIG. 11 illustrates screen 82 that is implemented to receive lodging information. FIG. 12 illustrates screen 84 that displays the total cost of the training program.

[0028] In the above example, the optimization module then generates the optimum solution selecting a combination of factors listed above for which the overall cost will be the lowest._As has been described in the above sections, the optimization module can be implemented in any computing device. An example computing device is described in FIG. 13.

[0029] FIG. 13 is a block diagram illustrating an example computing device 100 that is arranged for generating an optimum solution for a specific service. In a very basic configuration 102, computing device 100 typically includes one or more processors 104 and a system memory 106. A memory bus 124 may be used for communicating between processor 104 and system memory 106.

[0030] Depending on the desired configuration, processor 104 may be of any type including but not limited to a microprocessor (uP), a microcontroller (uC), a digital signal processor (DSP), or any combination thereof. Processor 104 may include one more levels of caching, such as a level one cache 110 and a level two cache 112, a processor core 114, and registers 116. An example processor core 114 may include an arithmetic logic unit (ALU), a floating point unit (FPU), a digital signal processing core (DSP Core), or any combination thereof. An example memory controller 118 may also be used with processor 104, or in some implementations memory controller 118 may be an internal part of processor 104.

[0031] Depending on the desired configuration, system memory 106 may be of any type including but not limited to volatile memory (such as RAM), non-volatile memory (such as ROM, flash memory, etc.) or any combination thereof. System memory 106 may include an operating system 120, one or more applications 122, and program data 124. Application 122 include an optimization module 120 that is arranged to determine an optimum solution for a requested service. Program data 126 may include a plurality of input parameters 110 that may be useful for various applications such as image processing as is described herein. In some embodiments, application 122 may be arranged to operate with program data 126 on operating system 120 such that an optimum solution is determined for a requested service. This described basic configuration 102 is illustrated in FIG. 1 by those components within the inner dashed line.

[0032]Computing device 100 may have additional features or functionality, and additional interfaces to facilitate communications between basic configuration 102 and any required devices and interfaces. For example, a bus/interface controller 130 may be used to facilitate communications between basic configuration 102 and one or more data storage devices 132 via a storage interface bus 138. Data storage devices 132 may be removable storage devices 134, non-removable storage devices 136, or a combination thereof. Examples of removable storage and non-removable storage devices include magnetic disk devices such as flexible disk drives and hard-disk drives (HDD), optical disk drives such as compact disk (CD) drives or digital versatile disk (DVD) drives, solid state drives (SSD), and tape drives to name a few. Example computer storage media may include volatile and nonvolatile, removable and non-removable media implemented in any method or technology for storage of information, such as computer readable instructions, data structures, program modules, or other data.

[0033] System memory 106, removable storage devices 134 and non-removable storage devices 136 are examples of computer storage media. Computer storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, digital versatile disks (DVD) or other optical storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium which may be used to store the desired information and which may be accessed by computing device 100. Any such computer storage media may be part of computing device 100.

[0034] Computing device 100 may also include an interface bus 138 for facilitating communication from various interface devices (e.g., output devices 140, peripheral interfaces 148, and communication devices 160) to basic configuration 102 via bus/ interface controller 130. Example output devices 142 include a graphics processing unit 144 and an audio processing unit 146, which may be configured to communicate to various external devices such as a display or speakers via one or more A/V ports 142. Example peripheral interfaces 148 include a serial interface controller 150 or a parallel interface controller 152, which may be configured to communicate with external devices such as input devices (e.g., keyboard, mouse, pen, voice input device, touch input device, etc.) or other peripheral devices (e.g., printer, scanner, etc.) via one or more I/O ports 148. An example communication device 160 includes a network controller 154, which may be arranged to facilitate communications with one or more other computing devices 158 over a network communication link via one or more communication ports 156.

[0035] The network communication link may be one example of a communication media. Communication media may typically be embodied by computer readable instructions, data structures, program modules, or other data in a modulated data signal, such as a carrier wave or other transport mechanism, and may include any information delivery media. A "modulated data signal" may be a signal that has one or more of its characteristics set or changed in such a manner as to encode information in the signal. By way of example, and not limitation, communication media may include wired media such as a wired network or direct-wired connection, and wireless media such as acoustic, radio frequency (RF), microwave, infrared (IR) and other wireless media. The term computer readable media as used herein may include both storage media and communication media.

[0036] Computing device 100 may be implemented as a portion of a small-form factor portable (or mobile) electronic device such as a cell phone, a personal data assistant (PDA), a personal media player device, a wireless web-watch device, a personal headset device, an application specific device, or a hybrid device that include any of the above functions. Computing device 100 may also be implemented as a personal computer including both laptop computer and non-laptop computer configurations.

[0037] The present disclosure is not to be limited in terms of the particular embodiments described in this application, which are intended as illustrations of various aspects. Many modifications and variations can be made without departing from its spirit and scope, as will be apparent to those skilled in the art. Functionally equivalent methods and apparatuses within the scope of the disclosure, in addition to those enumerated herein, will be apparent to those skilled in the art from the foregoing descriptions. Such modifications and variations are intended to fall within the scope of the appended claims. The present disclosure is to be limited only by the terms of the appended claims, along with the full scope of equivalents to which such claims are entitled. It is to be understood that this disclosure is not limited to particular methods, reagents, compounds compositions or biological systems, which can, of course, vary. It is also to be understood that the terminology used herein is for the purpose of describing particular embodiments only, and is not intended to be limiting.

[0038] With respect to the use of substantially any plural and/or singular terms herein, those having skill in the art can translate from the plural to the singular and/or from the singular to the plural as is appropriate to the context and/or application. The various singular/plural permutations may be expressly set forth herein for sake of clarity.

[0039] It will be understood by those within the art that, in general, terms used herein, and especially in the appended claims (e.g., bodies of the appended claims) are generally intended as "open" terms (e.g., the term "including" should be interpreted as "including but not limited to," the term "having" should be interpreted as "having at least," the term "includes" should be interpreted as "includes but is not limited to," etc.). It will be further understood by those within the art that if a specific number of an introduced claim recitation is intended, such an intent will be explicitly recited in the claim, and in the absence of such recitation no such intent is present. For example, as an aid to understanding, the following appended claims may contain usage of the introductory phrases "at least one" and "one or more" to introduce claim recitations. However, the use of such phrases should not be construed to imply that the introduction of a claim recitation by the indefinite articles "a" or "an" limits any particular claim containing such introduced claim recitation to embodiments containing only one such recitation, even when the same claim includes the introductory phrases "one or more" or "at least one" and indefinite articles such as "a" or "an" (e.g., "a" and/or "an" should be interpreted to mean "at least one" or "one or more"); the same holds true for the use of definite articles used to introduce claim recitations. In addition, even if a specific number of an introduced claim recitation is explicitly recited, those skilled in the art will recognize that such recitation should be interpreted to mean at least the recited number (e.g., the bare recitation of "two recitations," without other modifiers, means at least two recitations, or two or more recitations). Furthermore, in those instances where a convention analogous to "at least one of A, B, and C, etc." is used, in general such a construction is intended in the sense one having skill in the art would understand the convention (e.g., " a system having at least one of A, B, and C" would include but not be limited to systems that have A alone, B alone, C alone, A and B together, A and C together, B and C together, and/or A, B, and C together, etc.). In those instances where a convention analogous to "at least one of A, B, or C, etc." is used, in general such a construction is intended in the sense one having skill in the art would understand the convention (e.g., " a system having at least one of A, B, or C" would include but not be limited to systems that have A alone, B alone, C alone, A and B together, A and C together, B and C together, and/or A, B, and C together, etc.). It will be further understood by those within the art that virtually any disjunctive word and/or phrase presenting two or more alternative terms, whether in the description, claims, or drawings, should be understood to contemplate the possibilities of including one of the terms, either of the terms, or both terms. For example, the phrase "A or B" will be understood to include the possibilities of "A" or "B" or "A and B."

[0040] While only certain features of the invention have been illustrated and described herein, many modifications and changes will occur to those skilled in the art. It is, therefore, to be understood that the appended claims are intended to cover all such modifications and changes as fall within the true spirit of the invention.

CLAIMS:

1. A system for computing an optimum solution for a service, the system comprising:

one or more computing devices configured to enable a plurality of users to provide a plurality of input parameters to solicit one or more services;

a server system configured to communicate with the plurality of computing devices and configured to execute an optimization module, wherein the optimization module is configured to generate the optimum solution based on the plurality of input parameters and compute a lowest cost of the one or more services.

2. The system of claim 1, wherein the server system is configured to communicate with the plurality of computing devices via a telecommunication network.

3. The system of claim 1, wherein the plurality of input parameters comprise service parameters and infrastructure parameters.

4. The system of claim 3, wherein the optimization module is configured to determine one or more service providers for the solicited service.

5. The system of claim 4, wherein the optimization module is configured to obtain an availability of the one or more service providers based on the plurality of service parameters.

6. The system of claim 4, wherein the optimization module is configured to obtain an availability of the one or more facilities based on the plurality of infrastructure parameters.

7. The system of claim 3, wherein the optimization module is configured to generate a plurality of solutions with a corresponding ranking, each solution comprising combination of service providers and corresponding facilities.

8. The system of claim 7, wherein the ranking of the solution is based on a cost of each solution.

9. A system for computing an optimum solution for training program, the system comprising:
one or more computing devices configured to enable a plurality of users to provide a plurality of input parameters for the training program;

a server system configured to communicate with the plurality of computing devices and configured to execute an optimization module, wherein the optimization module is configured to generate the optimum cost for the training program based on the plurality of input parameters.

10. The system of claim 9, wherein the plurality of parameters comprise availability of a trainer and the plurality of users, location for the training program, travel costs for the plurality of trainers, accommodation cost, and the number of users.