The latest results of the Hungarian operations research community is reviewed based on the presentations given at the VOCAL 2022 conference. International collaborations and the continuation of research published at previous conferences of the series are also summarized.

The production schedule has a direct impact on the periodic utilization and energy consumption of equipment units. Meanwhile, for companies operating small power plants, the available renewable solar or wind energy changes continuously during the day, as does the hourly market price of the energy that can be purchased. Fortunately, the flexibility of production, possible schedules, or alternative recipes allow not only the minimization of costs but also the maximum use of renewable resources. The novelty of the P-graph-based method proposed here is the integration of three component problems into a single optimization model, namely the production scheduling by discrete event formulation, the management of flexible recipes by process synthesis, and the maximal renewable energy utilization according to discrete-time energy production and market price forecasts by representing them with temporarily available resources. The challenge of formalizing the optimization problem lies in synchronizing the time model of production scheduling with the resolution of market price and renewable energy production forecasts. The results show that the flexibility to alter both the sequence and schedule of operations by the integrated optimization model plays a critical role in optimizing energy usage.

The production of renewable fuels and chemicals is a critical component of global strategies to reduce greenhouse gas emissions. In this regard, pyrolysis oil obtained from biomass comprises hundreds of chemical compounds, thus rendering it a good precursor for manufacturing a variety of fuel products of commercial interest. Despite the large number of contributions describing the products' extraction, upgrading, and potential refining schemes, no bio-oil refinery is currently in operation. The main challenge in building a bio-oil refinery lies in the lack of an economically viable process configuration. Systematic studies comparing alternative refinery concepts, or configurations, are needed to identify the most promising configuration. To the best of our knowledge, this study is the first to use process graph (P-graph) methodology for the synthesis of pyrolysis oil refineries. In particular, this work shows the effectiveness of P-graph methodology in simultaneously calculating the profitability of various biorefinery designs by using data reported in the literature and providing information on how the introduction of new technologies to the database will impact the formation of profitable biorefinery concepts. Our work demonstrates a methodology for the addition of new unit operations to the database generated from the literature. The addition of a centrifuge for water extraction and a wet oxidation system for acetic acid production resulted in the generation of 330 biorefinery configurations, seven of which have a profitability ranging from $1,650 to $23,666/h (USD) with acetic acid and levoglucosan as the main products, respectively. This demonstrates that P-graph methodology is useful for discovering optimum techno-economic scenarios that may otherwise be overlooked.

Optimal clean process design requires strict constraints to enforce waste and byproduct management, all of which can be formulated in the language of mathematical programming. However, waste management and the utilization of by-products are often carried out in locations or periods other than the production process. The paper describes all modeling steps by P-graphs sufficient to represent raw material availability and production capacities in multiple time periods at multiple sites, as well as transportation and storage capacities of process materials and wastes. These steps are integrated into a single comprehensive model generation algorithm. For easier understanding, each model generation step is illustrated by a case study of planning a multi-site multi-period furniture production process alongside the recent challenges of energy supply and waste management. Finally, the case study of furniture production is analyzed under various circumstances to highlight the power of the proposed tools in daily production and transportation planning. Accordingly, the proposed method provides such alternative 5 best manufacturing and logistics plans that, in the event of a complete failure or overloading of one of the production capacities at either locations, there is still an alternative plan within a 3% profit decrease.