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The purpose of this paper is to provide an effective solution method for the truck and trailer routing problem (TTRP) which is one of the important NP-hard combinatorial optimization problems owing to its multiple real-world applications. It is a generalization of the famous vehicle routing problem (VRP), involving a group of geographically scattered customers served by the vehicle fleet including trucks and trailers.

The meta-heuristic solution approach based on bat algorithm (BA) in which a local search procedure performed by five different neighborhood structures is developed. Moreover, a self-adaptive (SA) tuning strategy to preserve the swarm diversity is implemented. The effectiveness of the proposed SA-BA is investigated by an experiment conducted on 21 benchmark problems that are well known in the literature.

Computational results indicate that the proposed SA-BA algorithm is computationally efficient through comparison with other existing algorithms found from the literature according to solution quality. As for the actual computational time, the SA-BA algorithm outperforms others. However, the scaled computational time of the SA-BA algorithm underperforms the other algorithms.

In this work the authors show that the proposed SA-BA is effective as a method for the TTRP problem. To the authors’ knowledge, the BA has not been applied previously, as in this work, to solve the TTRP problem.

A nurse home care scheduling system is described. The objective is to provide medical care at patients’ homes using the fewest number of nurses possible to deliver the required care. The heuristic scheduling system is easy to implement as a computerized adaptive system. As such, it is easy to use on a daily basis and easy to update as new data related to completed treatment and new requests are obtained. A case study illustrates the advantages of implementing such a system.

The purpose of this paper is to investigate US noncombatant evacuation operations (NEO) in South Korea and devise planning and management procedures that improve the efficiency of those missions.

It formulates a time-staged network model of the South Korean noncombatant evacuation system as a mixed integer linear program to determine an optimal flow configuration that minimizes the time required to complete an evacuation. This solution considers the capacity and resource constraints of multiple transportation modes and effectively allocates the limited assets across a time-staged network to create a feasible evacuation plan. That solution is post-processed and a vehicle routing procedure then produces a high resolution schedule for each individual asset throughout the entire duration of the NEO.

This work makes a clear improvement in the decision-making and resource allocation methodology currently used in a NEO on the Korea peninsula. It immediately provides previously unidentifiable information regarding the scope and requirements of a particular evacuation scenario and then produces an executable schedule for assets to facilitate mission accomplishment.

The significance of this work is not relegated only to evacuation operations on the Korean peninsula; there are numerous other NEO and natural disaster related scenarios that can benefit from this approach.

The purpose of this paper is to generate optimised trajectories for an unmanned aerial vehicle (UAV) during a forest fire detection mission. It is assumed that the UAV flies 3D curvature-constrained Dubins manoeuvres and has a limited amount of battery energy that prevents it from covering the entire search area in a single trip.

In this paper, the search area is discretised into a grid of multiple targets, and each target assigned with a score that is proportional to the time elapsed since the last UAV visit. This problem, known as Dubins Airplane Orienteering Problem, consists of finding the number and order of targets to visit and the UAV heading at each target that maximises the total trip score without exceeding the UAV battery energy. The solution is found using the Randomised Variable Neighbourhood Search metaheuristic. All target scores are updated after each trajectory generation according to the elapsed time since the last UAV visit.

The proposed approach produced feasible results when generating optimised trajectories for a fire detection mission context where energy battery constraints are important.

The authors carry out the planning of UAV missions with limited amounts of onboard energy such as a real fire detection mission using a single electric propulsion and fixed-wing UAV.

This paper introduces an energy-based approach to the Dubins Airplane Orienteering Problem, which takes into account the UAV performance and energy budget when generating optimised trajectories.

In the writers' view, an order processing system can best be built up by identifying the facilities required, and considering methods of order entry. They then discuss the advantages of telephone selling and describe how telephone sales operators can make full use of the order processing system to achieve maximum effectiveness.

Discusses the design of large‐scale distribution networks which entails taking decisions on a large number of issues that are all closely interrelated, making it difficult to develop a competitive distribution strategy. Many support systems for distribution planning have been developed, but, they do not facilitate a coherent approach to the design process. Presents a logistic planning system that provides dedicated support for all issues involved in distribution planning. The foundation of which is an integrated planning support framework. Proposes that small models dedicated to only part of the total design process provide the best support for logistic planning and that such models encapsulated in a framework lead to optimal system design. Suggests that when the support system is applied to strategic/tactical distribution planning, the design process requires less time and less expert capacity, while resulting in a more competitive logistic supply chain.

In this paper, the authors introduced a real world new problem, the multi-trip vehicle routing problem with time windows and the possible use of a less-than-truckload carrier to satisfy customer demands. The purpose of this paper is to develop a heuristic algorithm to route the private trucks with time windows and to make a selection between truckload and less-than-truckload carriers by minimizing a total cost function.

Both mathematical model and heuristic algorithm are developed for routing the private trucks with time windows and for selecting of less-than-truckload carriers by minimizing the total cost function.

In all, 40 test problems were examined with the heuristics. Computational results show that the algorithm obtains the optimal or near-optimal solutions efficiently in terms of time and accuracy.

The research described in this paper differs from the previous one on fleet planning or vehicle routing, in that it modifies the Clarke and Wright method by shifting the performance measure from a distance to cost and also incorporates the fixed cost of different types of trucks into the model. In addition, the authors simultaneously consider the multiple trip vehicle routing problems with time windows and the selection of less-than-truckload carriers that is an integrated scenario of real-world application. To the best of the authors’ knowledge, this scenario has not been considered in the literature.

Real time control and scheduling systems determine the vehicle routing plan based on the current status of the system. The status of a system can be represented by different attributes of demand such as location, quantity, and due date. The objective of this article is to propose a real time dynamic vehicle control and scheduling system for multi‐depot physical distribution. To perform the system objectives effectively, the proposed system includes five major modules. These are: global information collection system, depot controller, route planner, vehicle scheduler, vechicle route and time table feedback system. A simulation experiment is described at the end of the article to evaluate the performance of the proposed system. The results indicate that the proposed system is promising and can be implemented in practical operations.