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This paper considers a generalized version of the planar storage location problem arising in the stowage planning for Roll-on/Roll-off ships. A ship is set to sail along a predefined voyage where given cargoes are to be transported between different port pairs along the voyage. We aim at determining the optimal stowage plan for the vehicles stored on a deck of the ship so that the time spent moving vehicles to enable loading or unloading of other vehicles (shifting), is minimized. We propose a novel mixed integer programming model for the problem, considering both the stowage and shifting aspect of the problem. An adaptive large neighborhood search (ALNS) heuristic with several new destroy and repair operators is developed. We further show how the shifting cost can be effectively evaluated using Dijkstra’s algorithm by transforming the stowage plan into a network graph. The computational results show that the ALNS heuristic provides high quality solutions to realistic test instances. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

We consider a new problem of planning interrelated voyages with separation requirements along a single trade in roll-on roll-off shipping. Along a given trade with a sequence of port calls, there is a number of contracts for transportation of cargoes between the different port pairs, where each contract states its service frequency as well as that these services should be evenly separated in time. Instead of visiting all ports every time a trade is serviced, as closely resembles current planning practice, we aim at determining the sailing routes of each voyage along the trade, i.e. which ports to visit when, which contracts to serve, and the sailing speeds, so that all contract requirements regarding frequency and separation are satisfied at minimum cost. We propose and compare two novel mixed integer programming models for the problem, both including a new way of modeling the contracts’ separation requirements. Then we show through a computational study on a set of realistic test instances that significant gains can be obtained compared to current planning practice.

In this paper, we propose a mixed integer programming (MIP) model for the Chicken Flock Sizing, Allocation and Scheduling Problem (CFSASP), which is an important planning problem in the broiler production supply chain. To solve the CFSASP efficiently, two variants of rolling horizon heuristics (RHHs) have been developed and applied on the case of a Norwegian broiler production company. Computational results show that the RHHs successfully obtain high-quality solutions within a reasonable time. The value of optimisation is verified through comparison with the case company's plans, where the solutions from optimisation outperforms the current solutions. Sensitivity analyses are also conducted to provide managerial insights regarding certain strategic decisions, such as how many and which days to use for hatching of chickens. Due to the promising results, the case company is now implementing an optimisation-based decision support system based on the MIP model and solution methods shown in this paper. © 2020 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited, and is not altered, transformed, or built upon in any way.

Roll-on Roll-off shipping companies transport rolling cargo, such as cars, trucks and large construction machines. When sailing, this type of cargo must be attached to the deck using chains, to prevent damaging the cargo. For each voyage including multiple port calls where the cargo is loaded/unloaded, an important decision is to decide where to place each vehicle (or unit), such that the time used on shifting is minimized. Shifting means temporarily moving some vehicles to make an entry/exit route for the vehicles that are to be loaded/unloaded at a given port. As the vehicles are securely fastened to the deck, shifting is a time-consuming procedure. We present the stowage plan evaluation problem which is to determine the optimal vehicles to shift at each port call, such that the time spent on shifting is minimized. Given a set of alternative stowage plans for a voyage, the results from the stowage plan evaluation problems are used to determine the best among these stowage plans. We present a shortest path based heuristic for solving the problem. Computational results show that the solution method is a powerful tool for comparing stowage plans, due to its fast computing times and high success rate, i.e. its ability to determine the better of two stowage plans.

Roll-on/Roll-off (RoRo) ships represent the primary source for transporting vehicles and other types of rolling material over long distances. In this paper we focus on operational decisions related to stowage of cargoes for a RoRo ship voyage visiting a given set of loading and unloading ports. By focusing on stowage on one deck on board the ship, this can be viewed as a special version of a 2-dimensional packing problem with a number of additional considerations, such as one wants to place vehicles that belong to the same shipment close to each other to ease the loading and unloading. Another important aspect of this problem is shifting, which means temporarily moving some vehicles to make an entry/exit route for the vehicles that are to be loaded/unloaded at the given port. We present several versions of a new mixed integer programming (MIP) formulation for the problem. Computational results show that the model provides good solutions on small sized problem instances.