Feature-driven improvement of renewable energy forecasting and trading

M. A. Muñoz, J. M. Morales, and S. Pineda, Feature-driven Improvement of Renewable Energy Forecasting and Trading, IEEE Transactions on Power Systems, 2020.Inspired from recent insights into the common ground of machine learning, optimization and decision-making, this paper proposes an easy-to-implement, but effective procedure to enhance both the quality of renewable energy forecasts and the competitive edge of renewable energy producers in electricity markets with a dual-price settlement of imbalances. The quality and economic gains brought by the proposed procedure essentially stem from the utilization of valuable predictors (also known as features) in a data-driven newsvendor model that renders a computationally inexpensive linear program. We illustrate the proposed procedure and numerically assess its benefits on a realistic case study that considers the aggregate wind power production in the Danish DK1 bidding zone as the variable to be predicted and traded. Within this context, our procedure leverages, among others, spatial information in the form of wind power forecasts issued by transmission system operators (TSO) in surrounding bidding zones and publicly available in online platforms. We show that our method is able to improve the quality of the wind power forecast issued by the Danish TSO by several percentage points (when measured in terms of the mean absolute or the root mean square error) and to significantly reduce the balancing costs incurred by the wind power producer.European Research Council (ERC) under the EU Horizon 2020 research and innovation programme (grant agreement No. 755705) Spanish Ministry of Economy, Industry, and Competitiveness through project ENE2017-83775-P

Constructive solution methodologies to the capacitated newsvendor problem and surrogate extension

The newsvendor problem is a single-period stochastic model used to determine the order quantity of perishable product that maximizes/minimizes the profit/cost of the vendor under uncertain demand. The goal is to fmd an initial order quantity that can offset the impact of backlog or shortage caused by mismatch between the procurement amount and uncertain demand. If there are multiple products and substitution between them is feasible, overstocking and understocking can be further reduced and hence, the vendor\u27s overall profit is improved compared to the standard problem. When there are one or more resource constraints, such as budget, volume or weight, it becomes a constrained newsvendor problem. In the past few decades, many researchers have proposed solution methods to solve the newsvendor problem. The literature is first reviewed where the performance of each of existing model is examined and its contribution is reported. To add to these works, it is complemented through developing constructive solution methods and extending the existing published works by introducing the product substitution models which so far has not received sufficient attention despite its importance to supply chain management decisions. To illustrate this dissertation provides an easy-to-use approach that utilizes the known network flow problem or knapsack problem. Then, a polynomial in fashion algorithm is developed to solve it. Extensive numerical experiments are conducted to compare the performance of the proposed method and some existing ones. Results show that the proposed approach though approximates, yet, it simplifies the solution steps without sacrificing accuracy. Further, this dissertation addresses the important arena of product substitute models. These models deal with two perishable products, a primary product and a surrogate one. The primary product yields higher profit than the surrogate. If the demand of the primary exceeds the available quantity and there is excess amount of the surrogate, this excess quantity can be utilized to fulfill the shortage. The objective is to find the optimal lot sizes of both products, that minimize the total cost (alternatively, maximize the profit). Simulation is utilized to validate the developed model. Since the analytical solutions are difficult to obtain, Mathematical software is employed to find the optimal results. Numerical experiments are also conducted to analyze the behavior of the optimal results versus the governing parameters. The results show the contribution of surrogate approach to the overall performance of the policy. From a practical perspective, this dissertation introduces the applications of the proposed models and methods in different industries such as inventory management, grocery retailing, fashion sector and hotel reservation

Analysis of a two-echelon inventory system with two supply modes

In this paper, we consider a serial two-echelon periodic review inventory system with two supply modes at the most upstream stock point. As control policy for this system, we propose a natural extension of the dual-index policy, which has three base-stock levels. We consider the minimization of long run average inventory holding, backlogging, and both per unit and fixed emergency ordering costs. We provide nested newsboy characterizations for two of the three base-stock levels involved and show a separability result for the difference with the remaining base-stock level. We use results for the single-echelon system to efficiently approximate the distributions of random variables involved in the newsboy equations and find an asymptotically correct approximation for both the per unit and fixed emergency ordering costs. Based on these results, we provide an algorithm for setting base-stock levels in a computationally efficient manner. In a numerical study, we investigate the value of dual-sourcing in supply chains and show that it is useful to decrease upstream stock levels. In cases with high demand uncertainty, high backlogging cost or long lead times, we conclude that dual-sourcing can lead to significant savings

Dual Market Facility Network Design under Bounded Rationality

A number of markets, geographically separated, with different demand characteristics for different products that share a common component, are analyzed. This common component can either be manufactured locally in each of the markets or transported between the markets to fulfill the demand. However, final assemblies are localized to the respective markets. The decision making challenge is whether to manufacture the common component centrally or locally. To formulate the underlying setting, a newsvendor modeling based approach is considered. The developed model is solved using Frank-Wolfe linearization technique along with Benders’ decomposition method. Further, the propensity of decision makers in each market to make suboptimal decisions leading to bounded rationality is considered. The results obtained for both the cases are compared

Risk pooling via unidirectional inventory transshipments in a decentralized supply chain

We study risk pooling via unidirectional lateral transshipments between two locations under local decision-making. Unidirectional transshipments can be applicable when cost structures and/or capabilities differ between locations, and it is also a common practice in dual channel supply chains with online and offline sales channels. We show that such a system cannot be coordinated only with varying transshipment prices. The transshipment receiver orders more and the transshipment giver orders less than the respective optimal centralised order quantities. In order to remove this discrepancy, we suggest horizontal coordinationmechanisms by introducing a leftover subsidy for the location providing the transshipments or a shortage subsidy for the location receiving transshipments as well as a combination of shortage and leftover subsidy. Further, we evaluate the impact of network structure by comparing the equilibrium order quantities and profits under the uni- and bidirectional systems as well as a system without transshipments. Since demand correlation is a critical aspect in risk pooling we provide a detailed numerical study to discuss its impact on our findings

A review of non-cooperative newsvendor games with horizontal inventory interactions

There are numerous applications of game theory in the analysis of supply chains where multiple actors interact with each other in order to reach their own objectives. In this paper we review the use of non-cooperative game theory in inventory management within the newsvendor framework describing a single period inventory control model with the focus on horizontal interactions among multiple independent newsvendors. We develop a framework for identifying these types of horizontal interactions including, for example, the models with the possibility of inventory sharing via transshipments, and situations with substitutable products sold by multiple newsvendors. Based on this framework, we discuss and relate the results of prior research and identify future research opportunities

COOPERATION OR COMPETITION: A STUDY OF SOCIAL CAPITAL AND PRODUCTION DECISION UNDER POTENTIAL VERTICAL COMPETITION

Since the 2000s when retailers recognised the huge market potential, the growth of private labels has been unstoppable worldwide. As a result of the recession of national brands, manufacturers are in a relatively weaker position when dealing with large retailers. The relationship between manufacturers and retailers has transformed from pure cooperation to a delicate balance of cooperation and competition. Yet, how such a balance influences supply chain dynamics is an intriguing and overdue issue. This thesis explores the influence of social capital over manufacturers’ perceptions regarding their retailers’ trustworthiness in the presence of potential vertical competition, as well as the consequential performance from the perspective of cognitive abilities. Data was collected through an online scenario-based role play (SBRP) experiment, where 371 participants were recruited and put in three groups. In each group, participants were provided with a scenario depicting the product substitution level between a newly launched private label and a national brand. The data was analysed statistically to test the hypotheses. The results identify relational capital as the most influential dimension of social capital in suppressing manufacturer’s perception of opportunistic information sharing behaviour from retailers, and suggest that such suppression is moderated by the level of product substitution between private labels and national brands. This thesis has reference value to academia by looking into the overlapping issues of supply chain management and marketing and providing empirical evidence of the influences induced by the introduction of private labels. It also benefits industry, especially manufacturers, by giving a brief standard regarding whether to cooperate or compete when faced with potential vertical competition with retailers

Distribution-free Inventory Risk Pooling in a Multi-location Newsvendor

With rapidly increasing e-commerce sales, firms are leveraging the virtual pooling of online demands across customer locations in deciding the amount of inventory to be placed in each node in a fulfillment network. Such solutions require knowledge of the joint distribution of demands; however, in reality, only partial information about the joint distribution may be reliably estimated. We propose a distributionally robust multi-location newsvendor model for network inventory optimization where the worst-case expected cost is minimized over the set of demand distributions satisfying the known mean and covariance information. For the special case of two homogeneous customer locations with correlated demands, we show that a six-point distribution achieves the worst-case expected cost, and derive a closed-form expression for the optimal inventory decision. The general multi-location problem can be shown to be NP-hard. We develop a computationally tractable upper bound through the solution of a semidefinite program (SDP), which also yields heuristic inventory levels, for a special class of fulfillment cost structures, namely nested fulfillment structures. We also develop an algorithm to convert any general distance-based fulfillment cost structure into a nested fulfillment structure which tightly approximates the expected total fulfillment cost.https://deepblue.lib.umich.edu/bitstream/2027.42/146785/1/1389_Govindarajan.pd

On-demand last-mile distribution network design with omnichannel inventory

E-commerce delivery deadlines are getting increasingly tight, driven by a growing ‘I-want-it-now’ instant gratification mindset of consumers and the desire of online and omnichannel retailers to capitalize on the growth of on-demand e-commerce. On-demand deliveries with delivery deadlines as tight as one or two hours force companies to rethink their last-mile distribution network, since tight delivery deadlines require decentralization of order picking and inventory holding to ensure close proximity to consumers. This fundamentally changes the strategic design process of last-mile distribution networks. We study the impact of incorporating inventory order-up-to level decisions into the strategic design process of last-mile distribution networks with tight delivery deadlines. We develop an approximate inventory model by including an estimate of the cost of late delivery and additional transportation due to local stock-outs in a newsvendor formulation. Such local stock-outs require an order to be delivered from a more distant facility, which may lead to late delivery and additional transportation cost. We integrate our approximate inventory model and a location-allocation mixed-integer program that determines optimal facility locations, associated order-up-to inventory levels, and fleet composition, into a metamodel simulation-based optimization approach. Our numerical analyses demonstrate that pooling the additional online inventory with brick-and-mortar (B&M) inventories leads to cannibalization by the B&M network and higher B&M service levels. However, the pooling benefits to the online network outweigh the cost of inventory cannibalization. Furthermore, we show under which circumstances omnichannel retailers may have an incentive to consolidate online inventory in specific B&M facilities