Journal: TS Working Papers

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IVT, ETH Zurich

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20202
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Publications 1 - 2 of 2
  • The multi-commodity network flow problem with soft transit time constraints
    Item type: Working Paper
    Trivella, Alessio; Corman, Francesco; Koza, David Franz; et al. (2020)
    TS Working Papers
    The multi-commodity network flow problem (MCNF) consists in routing a set of commodities through a capacitated network at minimum cost and is relevant for routing containers in liner shipping networks. As commodity transit times are often a critical factor, the literature has introduced hard limits on commodity transit times. In practical contexts, however, these hard limits may fail to provide sufficient flexibility since routes with even tiny delays would be discarded. Motivated by a major liner shipping operator, we study an MCNF generalization where transit time restrictions are modeled as soft constraints, in which delays are discouraged using penalty functions of transit time. Similarly, early commodity arrivals can receive a discount in cost. We derive properties that distinguish this model from other MCNF variants and adapt a column generation procedure to efficiently solve it. Extensive numerical experiments conducted on realistic liner shipping instances reveal that the explicit consideration of penalty functions can lead to significant cost reductions compared to hard transit time deadlines. Moreover, the penalties can be used to steer the flow towards slower or faster configurations, resulting in a potential increase in operational costs, which generates a trade-off that we quantify under varying penalty functions.
  • Meeting corporate renewable power targets
    Item type: Working Paper
    Trivella, Alessio; Mohseni Taheri, Danial; Nadarajah, Selvaprabu (2020)
    TS Working Papers
    Prominent companies have committed to procuring a percentage of their power demand from renewable sources by a future date. Long-term financial contracts with renewable generators, known as corporate power purchase agreements (CPPAs), are popular to meet such a renewable power purchase target (RPPT). By analyzing a simplified three-stage model, we show that the generation capacity contracted via a CPPA is more nuanced to structure optimally compared to traditional long-term power contracts due to the interplay between price and supply uncertainties as well as the RPPT. We subsequently propose a Markov decision process (MDP) to formalize rolling-power- purchase policies used in practice, that is, the construction of dynamic CPPA portfolios to meet an RPPT. The optimal MDP policy is intractable to compute but possesses the following key properties: (i) its decisions account for stochastic prices and supply, (ii) it captures the timing flexibility to enter CPPAs, and (iii) it can sign CPPAs with different tenures. We develop forecast-based reoptimization heuristics and a novel information-relaxation based reoptimization approach that sacrifice and approximate, respectively, the first property of the MDP policy and capture the remaining properties. We perform an extensive computational study on realistic procurement instances to uncover managerial insights related to procurement costs, the control of risks arising from supply uncertainty, the relevance of CPPAs as markets evolve, and the near-optimality of rolling power purchases from our information-relaxation based procurement heuristic.
Publications 1 - 2 of 2