ORDINA BLOGT

Planning optimization

From theory to practice…

  • Osman Ali
  • 3 december 2013

Is optimization of real-life planning problems becoming a reality? This has remained an open question from industry, which is eager to optimize their supply chains - longing to cut costs and increases profitability. While academics take pride in their analytical modeling approaches to  support planning and decision making, industry is often faced with difficulties to translate those theories into workable solutions. 

Typically, analytical modeling approaches involve constructing mathematical models that attempt to describe the planning problem. These models enable solving planning cases for predetermined objectives, with an aim to find optimal or near-optimal solutions. Since the search for an optimal solution is combinatorial in nature, the optimization process can become quickly burdensome in terms of computational time and effort. To date, this remains a primary hurdle in applying such optimization approaches to real-life problems. Having said that, due to substantial advancements in IT, it is now common to find powerful computing platforms with parallel processing capacities and immense amounts of memory. These advancements greatly facilitate the computation intensive tasks involved in optimization.

Recognizing the potential of planning optimization for industry, in the last years, the APS (advanced planning and scheduling ) team at Ordina has taken up several planning optimization cases of clients in production, logistics and service sectors. Each case involved complex decision making over midterm planning horizons, typically, between 1 to 3 months. The optimization solutions developed are successfully deployed at clients, who reported to have greatly benefited from them. These solutions facilitate planners in the cumbersome activity of solving their complex planning puzzles. They automates many of the manual tasks involved in the planning, and generate valuable results in comparatively much less time. Furthermore, due to the quantitative nature of the optimization models, the planning results are generated with quantifiable indication of the quality of the solution. The planners can see the influence of their input parameters on the planning results, and can run multiple simulations to get the results that matches the planning objectives.

Thanks to the positive feedback and increasing interest from clients, the APS team keeps on investing in its people and solutions to make every new solution better than the last. This means our solutions are continuously evolving, which keeps the APS-team a very interesting and challenging team to work with. Witnessing our clients create value and comparative advantages thanks to the solutions we build for them, is a very rewarding experience.

Over de auteur:

Osman Ali

Bedrijven die op grote schaal mensen en middelen inplannen, moeten bij Osman zijn. Hij is gespecialiseerd in het oplossen van planning-problemen, bijvoorbeeld in de logistieke en medische sector.