The current decade sees a considerable growth in worldwide container transportation and with it an indispensable need for optimization. Also the interest in and availability of academic literatures as well as case reports are almost exploding. With this paper an earlier survey which proved to be of utmost importance for the community is updated and extended to provide the current state of the art in container terminal operations and operations research.

Operations research at container terminals: a literature update

The objective of this paper is to review the current status of ship routing and scheduling. We focus on literature published during the last decade. Because routing and scheduling problems are closely related to many other fleet planning problems, we have divided this review into several parts. We start at the strategic fleet planning level and discuss the design of fleets and sea transport systems. We continue with the tactical and operational fleet planning level and consider problems that comprise various ship routing and scheduling aspects. Here, we separately discuss the different modes of operations: industrial, tramp, and liner shipping. Finally, we take a glimpse at naval applications and other related problems that do not naturally fall into these categories. The paper also presents some perspectives regarding future developments and use of optimization-based decision-support systems for ship routing and scheduling. Several of the trends indicate both accelerating needs for and benefits from such systems and, hopefully, this paper will stimulate further research in this area.

https://www.jstor.org/stable/pdfplus/25769174.pdf

Ship Routing and Scheduling: Status and Perspectives

This paper is the second part of a comprehensive survey on pickup and delivery models. Basically, two problem classes can be distinguished. The first part dealt with the transportation of goods from the depot to linehaul customers and from backhaul customers to the depot. In this class four subtypes were considered, namely the Vehicle Routing Problem with Clustered Backhauls (VRPCB all linehauls before backhauls), the Vehicle Routing Problem with Mixed linehauls and Backhauls (VRPMB any sequence of linehauls and backhauls permitted), the Vehicle Routing Problem with Divisible Delivery and Pickup (VRPDDP customers demanding delivery and pickup service can be visited twice), and the Vehicle Routing Problem with Simultaneous Delivery and Pickup (VRPSDP customers demanding both services have to be visited exactly once). The second part now considers all those problems where goods are transported between pickup and delivery locations, denoted as Vehicle Routing Problems with Pickups and Deliveries (VRPPD). These are the Pickup and Delivery VRP (PDVRP unpaired pickup and delivery points), the classical Pickup and Delivery Problem (PDP paired pickup and delivery points), and the Dial-A-Ride Problem (DARP paired pickup and delivery points and user inconvenience taken into consideration). A single as well as a multi vehicle mathematical problem formulation for all three VRPPD types is given, and the respective exact, heuristic, and metaheuristic solution methods are discussed.

/pdf/a-survey-on-pickup-and-delivery-problems-part-ii-s8djcjjy1t.pdf

A survey on pickup and delivery problems: Part II: Transportation between pickup and delivery locations

Pickup and delivery problems constitute an important class of vehicle routing problems in which objects or people have to be collected and distributed. This paper introduces a general framework to model a large collection of pickup and delivery problems, as well as a three-field classification scheme for these problems. It surveys the methods used for solving them.

Static pickup and delivery problems: a classification scheme and survey

This paper is the first part of a comprehensive survey on pickup and delivery problems. Basically, two problem classes can be distinguished. The first class, discussed in this paper, deals with the transportation of goods from the depot to linehaul customers and from backhaul customers to the depot. This class is denoted as Vehicle Routing Problems with Backhauls (VRPB). Four subtypes can be considered, namely the Vehicle Routing Problem with Clustered Backhauls (VRPCB – all linehauls before backhauls), the Vehicle Routing Problem with Mixed linehauls and Backhauls (VRPMB – any sequence of linehauls and backhauls permitted), the Vehicle Routing Problem with Divisible Delivery and Pickup (VRPDDP – customers demanding delivery and pickup service can be visited twice), and the Vehicle Routing Problem with Simultaneous Delivery and Pickup (VRPSDP – customers demanding both services have to be visited exactly once). The second class, dealt with in the second part of this survey, refers to all those problems where goods are transported between pickup and delivery locations. These are the Pickup and Delivery Vehicle Routing Problem (PDVRP – unpaired pickup and delivery points), the classical Pickup and Delivery Problem (PDP – paired pickup and delivery points), and the Dial-A-Ride Problem (DARP – passenger transportation between paired pickup and delivery points and user inconvenience taken into consideration). Single as well as multi vehicle versions of the mathematical problem formulations are given for all four VRPB types, the corresponding exact, heuristic, and metaheuristic solution methods are discussed.

/pdf/a-survey-on-pickup-and-delivery-problems-4jg10ds2xx.pdf

A survey on pickup and delivery problems

Here, we describe a real planning problem in the tramp shipping industry. A tramp shipping company may have a certain amount of contract cargoes that it is committed to carry, and tries to maximize the profit from optional cargoes. For real long-term contracts, the sizes of the cargoes are flexible. However, in previous research within tramp ship routing, the cargo quantities are regarded as fixed. We present an MP-model of the problem and a set partitioning approach to solve the multi-ship pickup and delivery problem with time windows and flexible cargo sizes. The columns are generated a priori and the most profitable ship schedule for each cargo set–ship combination is included in the set partitioning problem. We have tested the method on several real-life cases, and the results show the potential economical effects for the tramp shipping companies by utilizing flexible cargo sizes when generating the schedules.

https://link.springer.com/content/pdf/10.1057%2Fpalgrave.jors.2602263.pdf

Ship routing and scheduling with flexible cargo sizes

We consider a combined time constrained ship routing and inventory managementproblem. A fleet of ships transports a single product between production and consumptionharbours. The transporter has the responsibility for keeping the stock level within its limitsat all actual harbours, and there should be no need to stop the production at any harboursdue to missing transportation possibilities. The number of arrivals to each harbour and thequantities loaded and discharged at each arrival are determined by the continuous productionrates at the harbours, the stock limits and the actual ships visiting the harbours. We use apath flow formulation for this planning problem, and generate paths for each ship includinginformation about the geographical route, the load quantity and start time at each harbourarrival. In addition, we generate paths for each harbour including information about thenumber of arrivals to the harbour, the load quantity and start time at each harbour arrival.We emphasise the formulation of the path generation problems which are subproblems inthe total planning problem. The generated paths appear as columns in a path flow problemwhich corresponds to a master problem. We use a column generation approach to solve thecontinuous problem. The solution is made integer optimal by branch-and-bound. Computationalresults indicate that a path flow formulation and an optimisation based solutionapproach work for real instances of the planning problem.

Modelling path flows for a combined ship routingand inventory management problem

In the continental shelf off the coast of Norway, there are several petroleum fields containinga mixture of oil and gas. A multiperiod mixed integer programming model for investmentplanning for these fields has been used by The Norwegian Petroleum Directorate for morethan fifteen years. In practical use, the production from each field has mostly been declaredto follow profiles given by the user, but the user may also declare that the production canvary from the given profile. This paper describes the model and comments on some of thereal problems the model has been used to analyze and the modeling process involved.

Modeling Norwegian petroleum productionand transportation

Tactical planning of offshore petroleum production

We consider a real integrated ship scheduling and inventory management problem. A fleet of ships transports a single product between production and consumption plants. The transporter has the responsibility for keeping the inventory level within its limits at all actual plants, and there should be no need to stop the production at any plants caused by missing transportation possibilities.

Bjørn Nygreen

Papers

Ship routing and scheduling with flexible cargo sizes

Modelling path flows for a combined ship routingand inventory management problem

Modeling Norwegian petroleum productionand transportation

Tactical planning of offshore petroleum production

Robust Inventory Ship Routing by Column Generation