1. Wit Jakuczun, PhD – CEO at WLOG Solutions wit.jakuczun@wlogsolutions.pl Optimization with R Bringing the Power of LocalSolver to R: a Real-Life Case-Study

2. Wit Jakuczun, PhD – CEO at WLOG Solutions wit.jakuczun@wlogsolutions.pl Diversity challenges at WLOG Solutions finance, logistics, production, telecoms, public Industries: on-site, near shore, off shore Delivery models: consulting, solution implementation, training Contract types: data fusion, prediction, visualization, simulation, optimization Analytical problems:

3. Wit Jakuczun, PhD – CEO at WLOG Solutions wit.jakuczun@wlogsolutions.pl

4. Wit Jakuczun, PhD – CEO at WLOG Solutions wit.jakuczun@wlogsolutions.pl One size does not fit all Software ecosystems: R, SAS, Python, JavaScript, PHP, Java, C++, … Optimization: LocalSolver, Gurobi, IBM (ILOG), Sicstus, ECLiPSe, COIN-OR, GLPK

5. Wit Jakuczun, PhD – CEO at WLOG Solutions wit.jakuczun@wlogsolutions.pl Optimization tool heaven for R Seamless to wrap into R processing workflow Separation of model and data specification High level definition of optimization task Swiss army knife (we would love to get a free lunch ) Reliable support and continued development Free and open-source

6. Wit Jakuczun, PhD – CEO at WLOG Solutions wit.jakuczun@wlogsolutions.pl LOCALSOLVER PACKAGE

7. Wit Jakuczun, PhD – CEO at WLOG Solutions wit.jakuczun@wlogsolutions.pl localsolver package architecture Solution presentation GNU R (e.g. shiny app) Solving LocalSolver engine Model building LSP language Data preparation GNU R

8. Wit Jakuczun, PhD – CEO at WLOG Solutions wit.jakuczun@wlogsolutions.pl LocalSolver engine Innovative math modeling language New generation hybrid solver

9. Wit Jakuczun, PhD – CEO at WLOG Solutions wit.jakuczun@wlogsolutions.pl Why localsolver package? Current optimization packages Many tools for one task Low level API Low performance Restricted modelling approach localsolver package One tool for many tasks High-level API High performance Wide range of applications What we got: Shorter projects Simpler to debug Lower delivery costs

10. Wit Jakuczun, PhD – CEO at WLOG Solutions wit.jakuczun@wlogsolutions.pl Solving k-medoids: a comparison Rglpk 45 LOC 1 hour including „stupid” bugs Need to populate constraint matrix from R’s data structures No high-level math modelling language localsolver 18 LOC 15 minutes spent mostly inventing model Staying with R’s data structures Flexible high-level math modelling language http://rsnippets.blogspot.com/2014/07/comparing-localsolver-with-rglpk-on-k.html

11. Wit Jakuczun, PhD – CEO at WLOG Solutions wit.jakuczun@wlogsolutions.pl LOGISTIC NETWORK PLANNING FOR POULTRY MEAT PRODUCER

12. Wit Jakuczun, PhD – CEO at WLOG Solutions wit.jakuczun@wlogsolutions.pl Poultry meat logistic network planning problem Factories 3 locations Warehouses 18 locations 3 different sizes Customers 3000 locations Products 2 types (fresh, processed) thousands of SKUs Choose optimal locations and capacities of warehouses

13. Wit Jakuczun, PhD – CEO at WLOG Solutions wit.jakuczun@wlogsolutions.pl THANK YOU!