Tag Archives: job

Research Assistant Professor position at University of Miami’s School of Business

My department is hiring! :-) See details below.

The Management Science Department at the University of Miami’s School of Business Administration invites applications for a non-tenure-track Research Assistant Professor position to begin in the Fall of 2015. The Management Science Department is a diverse group of faculty with expertise in several areas within Operations Research and Analytics, including statistics and machine learning, optimization, simulation, and quality management. Duties will include research, teaching at both the graduate and undergraduate levels, and advising undergraduate students seeking majors/minors in Management Science or Business Analytics.

Applicants should possess a PhD in operations research or a related discipline by the start date of employment. Applications should be submitted by e-mail to facultyaffairs@bus.miami.edu, and should include the following: a curriculum vitae, up to three representative publications, brief research and teaching statements, an official graduate transcript, information about teaching experience and performance evaluations, and three letters of recommendation. Applications will be reviewed as they arrive. The position will remain open until filled.

The University of Miami offers a comprehensive benefits package including medical and dental benefits, tuition remission, vacation, paid holidays, and much more. The University of Miami is an Equal Opportunity/Affirmative Action Employer.

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Tenure-Track Position in Big Data Analytics, University of Miami, School of Business

I’m very happy to announce that the School of Business at the University of Miami is hiring in my department! Details below. This is an exciting time to be involved in Business Analytics!

Tenure-Track Faculty Position in Management Science (Big Data Analytics)

The Management Science Department at the University of Miami’s School of Business Administration invites applications for a tenure-track faculty position at the junior or advanced Assistant Professor level to begin in the Fall of 2015. Exceptional candidates at higher ranks will be considered subject to additional approval from the administration. Salaries are extremely competitive and commensurate with background and experience. This is a nine-month appointment but generous summer research support is anticipated from the School of Business.

Applicants with research interests in all areas of Analytics will be considered, although primary consideration will be given to those with expertise in Big Data Analytics and the computational challenges of dealing with large data sets. Expertise in, or experience with, one or more of the following is particularly welcome: MapReduce/Hadoop, Mahout, Cassandra, cloud computing, mobile/wearable technologies, social media analytics, recommendation systems, data mining and machine learning, and text mining. The Management Science Department is a diverse group of faculty with expertise in several areas within Operations Research and Analytics, including statistics and machine learning, optimization, simulation, and quality management. Duties will include research and teaching at the graduate and undergraduate levels.

Applicants should possess, or be close to completing, a PhD in computer science, operations research, statistics, or a related discipline by the start date of employment. Applications should be submitted by e-mail to facultyaffairs@bus.miami.edu, and should include the following: a curriculum vitae, up to three representative publications, brief research and teaching statements, an official graduate transcript (for the junior Assistant Professor level), information about teaching experience and performance evaluations, and three letters of recommendation. All applications completed by December 1, 2014 will receive full consideration, but candidates are urged to submit all required material as soon as possible. Applications will be accepted until the position is filled.

The University of Miami offers a comprehensive benefits package including medical and dental benefits, tuition remission, vacation, paid holidays, and much more. The University of Miami is an Equal Opportunity/Affirmative Action Employer.

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The Joy of Baking (Optimally)

‘Tis the season of baking all kinds of things: cookies, cakes, breads, brownies, pies, and my favorite Brazilian dessert “pudim de leite moça“, which is depicted below. Click here for the step-by-step recipe.

Many OR bloggers, such as Laura McLay and Anna Nagurney, actually enjoy baking, and they both have written posts on the subject (e.g. here and here). I happen to include myself in this group and, yes, I made the pudim shown above (using  my mom’s recipe).

My goal today is to approach the art of baking from an optimization point of view. Let’s say you have a long list of items to bake. Perhaps you’re hosting a mega party at your house, or you’re helping your local church or favorite charity with their holiday cooking. You have an oven that can only fit so much at a time (think of area, or volume). Each item to be baked occupies some space in the oven and needs to bake for a specific amount of time. In what order should you bake your items so that you finish as soon as possible? (Side note: it may not be obvious at first sight, but this is the same problem faced by a container port that needs to decide the order in which to unload cargo ships.)

In the OR world, this is a job scheduling problem with a cumulative machine. The jobs are the tasks to be performed (items to bake), the machine (or resource) is the oven. We say the oven is cumulative, as opposed to disjunctive, because it can deal with (bake) multiple items at a time. The unknowns in this optimization problem are the start times of each job (when to begin baking each item). The objective is to minimize the makespan, which is defined as the finish time of the last job (the time at which it’s OK to turn off the oven). Finally, this is a non-preemptive problem because, typically, once you start baking something, it stays in the oven until it’s done.

This problem occurs so often in practice that the Constraint Programming (CP) community created a global constraint to represent it. It’s called the cumulative constraint (what a surprise!). Here’s a reference. For example, let’s say that we have a 10-cubic-foot (cf) oven and we need to bake five items. The baking times (in minutes) are 20, 25, 40, 30, and 30. The space requirements in cf are, respectively, 6, 4, 5, 6, 4. If the time at which we begin baking item i is denoted by the variable s_i, we can write the following in a CP model:

\mathrm{cumulative}([s_1,s_2,s_3,s_4,s_5],[20,25,40,30,30],[6,4,5,6,4],10)

The above constraint makes sure that the start times s_i are such that the capacity of the oven is never exceeded. To minimize the makespan, we have to minimize the maximum among s_1+6, s_2+4, s_3+5, s_4+6, and s_5+4.

It’s easy to incorporate some real-life details into this model. For example:

  • Not every item will be ready to go into the oven at time zero. After all, you’re making them as you go. To take care of this, add a ready-time r_i (i.e. a lower bound) to the appropriate variable: r_i \leq s_i.
  • If a given item does not occupy the entire oven, but you still prefer to bake it alone, just artificially increase its space requirement c_i to be equal to the oven’s capacity C.
  • If you’re baking both savory and sweet things, you probably don’t want to mix them up in the oven. In that case, simply solve the problem twice.
  • If, for some reason, item i must be finished before item j starts baking (e.g. they need different temperatures), just include the constraint s_i + p_i \leq s_j, where p_i is the baking time of item i.

We could, of course, have approached this problem from an Integer Programming point of view. In that case, we’d have binary variables x_{it} that are equal to 1 if you start baking item i at time t, and equal to zero otherwise. For more details on this formulation, including model files and some pretty tough instances, take a look at the CuSPLIB web page.

In the spirit of holiday baking, I will close with some pictures of past baking jobs ran on my house’s machine (a.k.a. oven). Enjoy! :-)

Key Lime Pie

Carrot Oatmeal Cookies (recipe here)

Sparkling Ginger Chip Cookies (recipe here)

Irish Soda Bread

Six-Seed Soda Bread (recipe here)


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Filed under Applications, Constraint Programming, CuSPLIB, Food, Holidays, INFORMS Monthly Blog Challenge, Integer Programming, Modeling, People

Introducing CuSPLIB

A couple of colleagues and I are doing research on single-machine cumulative scheduling problems (CuSP). As part of this effort, we’ll have to create some benchmark instances on which to test our algorithms. Some time ago, I searched around for problem instances and could not find any. People seem to be more interested in the Resource Constrained Project Scheduling Problem (RCPSP), of which the CuSP is a special case/subproblem. One of the experts in the area told me that he was unaware of any standard CuSP benchmarks and that difficult instances were hard to generate. Therefore, I decided to make our instances public, hoping that (i) this could be helpful/useful to someone else out there, and (ii) this could attract more attention to this problem. As a result, CuSPLIB is born! It includes a few pieces of code (instance generator, MIP and CP models), an initial set of 10 instances, and some discussion about integer programming models for the problem. I intend to talk about other (alternative) models and include some references in the near future. The preliminary computational results are interesting and make me believe that it’s not that difficult to find challenging instances. Let me know what you think, and feel free to contribute to CuSPLIB! I’ll be updating it little by little as our research progresses.

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Filed under Constraint Programming, CuSPLIB, Integer Programming, Modeling, Research