School timetabling problem under disturbances

School timetables are one or multiple times per year generated to assign class-teacher combinations to class rooms and timeslots. Post-publication disturbances such as absence of teachers typically pose a need for schedulers to rapidly implement some minor changes to avoid empty periods in the timetable. In this paper our aim is to define methods to efficiently solve the school timetabling problem under disturbances. We present three types of solution methods, namely a simple rule-of-thumb, a heuristic and an optimization approach. Exhaustive numerical experiments have been performed with data from five high schools in The Netherlands, each with their unique characteristics in number of classes, number of teachers and number of daily meetings. For each of the three methods we show advantages and disadvantages as well as the effects of resulting changes in the schedules.<br/

Design of Cross-chain Internet Order Fulfillment Centres

Many consumers have embraced the option of ordering via the Internet, which has resulted in an enormous increase in direct orders compared to the times when direct ordering was done by catalogue and phone. The fulfillment process in the supply chain is an important factor for these consumers impacting how long they must wait between ordering and delivery. This fact has significantly increased the importance of the back-end fulfillment process. We present a novel supply chain design to enable cross-chain coordination of order fulfillment operations for internet sales. Shared warehousing facilities are used more and more to achieve competitive advantage. This situation asks for new models to enable a smooth warehousing process for each web shop, but at the same time to ensure overall efficiency and effectiveness. This paper introduces a layout model for shared operations under one roof by simultaneously optimizing the overall facility layout and the area layout

Integration of returns and decomposition of customer orders in e-commerce warehouses

In picker-to-parts warehouses, order picking is a cost- and labor-intensive operation that must be designed efficiently. It comprises the construction of order batches and the associated order picker routes, and the assignment and sequencing of those batches to multiple order pickers. The ever-increasing competitiveness among e-commerce companies has made the joint optimization of this order picking process inevitable. Inspired by the large number of product returns and the many but small-sized customer orders, we address a new integrated order picking process problem. We integrate the restocking of returned products into regular order picking routes and we allow for the decomposition of customer orders so that multiple batches may contain products from the same customer order. We thereby generalize the existing models on order picking processing. We provide Mixed Integer Programming (MIP) formulations and a tailored adaptive large neighborhood search heuristic that, amongst others, exploits these MIPs. We propose a new set of practically-sized benchmark instances, consisting of up to 5547 to be picked products and 2491 to be restocked products. On those large-scale instances, we show that integrating the restocking of returned products into regular order picker routes results in cost-savings of 10 to 15%. Allowing for the decomposition of the customer orders' products results in cost savings of up to 44% compared to not allowing this. Finally, we show that on average cost-savings of 17.4% can be obtained by using our ALNS instead of heuristics typically used in practice.Comment: Authors' preprin

Towards Low-carbon Power Networks: Optimal Integration of Renewable Energy Sources and Hydrogen Storage

This paper proposes a new optimization model and solution method for determining optimal locations and sizing of renewable energy sources and hydrogen storage in a power network. We obtain these strategic decisions based on the multi-period alternating current optimal power (AC OPF) flow problem that considers the uncertainty of renewable output, electricity demand, and electricity prices. We develop a second-order cone programming approach within a Benders decomposition framework to provide globally optimal solutions. To the best of our knowledge, our paper is the first to propose a systematic optimization framework based on AC OPF that jointly analyzes power network, renewable, and hydrogen storage interactions in order to provide optimal locations and sizing decisions of renewables and hydrogen storage. In a test case, we show that the joint integration of renewable sources and hydrogen storage and consideration of the AC OPF model significantly reduces the operational cost of the power network. In turn, our findings can provide quantitative insights to decision-makers on how to integrate renewable sources and hydrogen storage under different settings of the hydrogen selling price, renewable curtailment costs, emission tax prices, and conversion efficiency

Integration of returns and decomposition of customer orders in e-commerce warehouses

In picker-to-parts warehouses, order picking is a cost- and labor-intensive operation that must be designed efficiently. It comprises the construction of order batches and the associated order picker routes, and the assignment and sequencing of those batches to multiple order pickers. The ever-increasing competitiveness among e-commerce companies has made the joint optimization of this order picking process inevitable. Inspired by the large number of product returns and the many but small-sized customer orders, we address a new integrated order picking process problem. We integrate the restocking of returned products into regular order picking routes and we allow for the decomposition of customer orders so that multiple batches may contain products from the same customer order. We thereby generalize the existing models on order picking processing. We provide Mixed Integer Programming (MIP) formulations and a tailored adaptive large neighborhood search heuristic that, amongst others, exploits these MIPs. We propose a new set of practically-sized benchmark instances, consisting of up to 5547 to be picked products and 2491 to be restocked products. On those large-scale instances, we show that integrating the restocking of returned products into regular order picker routes results in cost-savings of 10 to 15%. Allowing for the decomposition of the customer orders' products results in cost savings of up to 44% compared to not allowing this. Finally, we show that on average cost-savings of 17.4% can be obtained by using our ALNS instead of heuristics typically used in practice.Comment: Authors' preprin

A dynamic thompson sampling hyper-heuristic framework for learning activity planning in personalized learning

Personalized learning is emerging in schools as an alternative to one-size-fits-all education. This study introduces and explores a weekly demand-driven flexible learning activity planning problem of own-pace own-method personalized learning. The introduced problem is a computationally intractable optimization problem involving many decision dimensions and also many soft constraints. We propose batch and decomposition methods to generate good-quality initial solutions and a dynamic Thompson sampling based hyper-heuristic framework, as a local search mechanism, which explores the large solution space of this problem in an integrative way. The characteristics of our test instances comply with average secondary schools in the Netherlands and are based on expert opinions and surveys. The experiments, which benchmark the proposed heuristics against Gurobi MIP solver on small instances, illustrate the computational challenge of this problem numerically. According to our experiments, the batch method seems quicker and also can provide better quality solutions for the instances in which resource levels are not scarce, while the decomposition method seems more suitable in resource scarcity situations. The dynamic Thompson sampling based online learning heuristic selection mechanism is shown to provide significant value to the performance of our hyper-heuristic local search. We also provide some practical insights; our experiments numerically demonstrate the alleviating effects of large school sizes on the challenge of satisfying high-spread learning demands.</p

Port supply chain integration:analyzing biofuel supply chains

This paper focuses on port supply chain integration to strengthen operational and business performance. We provide a structured and comprehensive method to enable port supply chain integration and demonstrate its applicability to the biofuel supply chain. We define the value proposition, role, activities, resources, and characteristics that a port needs to integrate in the biofuel supply chain and incorporate them in an 'integration matrix'. Port authorities can achieve integration in the biofuel supply chain by extending their role and (1) facilitating flows, (2) attracting new flows, (3) executing value-adding activities, (4) developing a bio-industry cluster, and (5) acting as a knowledge center. A roundtable and two single case studies on the Port of Rotterdam and the northern Dutch port cluster have validated the content and applicability of our findings.</p