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

Ship routing and scheduling in the new millennium

Publisher Summary This chapter discusses various aspects of maritime transportation operations and presents associated decision-making problems and models with an emphasis on ship routing and scheduling models. The chapter describes prescriptive operations research (OR) models and associated methodologies, rather than descriptive models that are usually of interest to economists and public policy makers. The ocean shipping industry has a monopoly on transportation of large volumes of cargo among continents. Pipeline is the only transportation mode that is cheaper than ships for moving large volumes of cargo over long distances. Maritime transportation is the backbone of international trade. The volume of maritime transportation has been growing for many years and is expected to continue growing in the foreseeable future. Maritime transportation is a unique transportation mode possessing characteristics that differ from other modes of transportation and requires decision support models that fit the specific problem characteristics. Maritime transportation poses a wide variety of challenging research problems, the solutions to which have high potential to improve economic performance and increase profitability in the highly competitive arena.

Chapter 4 Maritime Transportation

We present an optimisation-based solution approach for a real ship planning problem,which is a combination of a variant of the multi-vehicle pickup and delivery problemwith time windows (m-PDPTW), and a multi-inventory model This problem involves thedesign of a set of minimum cost routes for a fleet of heterogeneous ships servicing a set ofproduction and consumption harbours with a single product (ammonia) The production andinventory information at each harbour, together with the ship capacities and the location ofthe harbours, determine the number of possible arrivals at each harbour during the planningperiod, the time windows for start of service and the load quantity intervals at each arrivalWe call this problem the inventory pickup and delivery problem with time windows -IPDPTW In the mathematical programming model, we duplicate some of the variables anduse a Dantzig - Wolfe decomposition approach Then the IPDPTW decomposes into a sub-problemfor each harbour and each ship By synchronising the solutions from both types ofsubproblems, we get extra constraints in the master problem as compared to the masterproblem for the m-PDPTW discussed in the literature The LP-relaxation of the masterproblem is solved by column generation, where the columns represent ship routes or harbourvisit sequences Finally, this iterative solution process is embedded in a branch-and-boundsearch to make the solution integer optimal Our computational results indicate that theproposed method works for the real planning problem

Bjørn Nygreen

Papers

Ship routing and scheduling in the new millennium

Chapter 4 Maritime Transportation

A method for solving ship routing problemswith inventory constraints

A multi-start local search heuristic for ship scheduling—a computational study

Column generation approaches to ship scheduling with flexible cargo sizes