Sin C. Ho

A tabu search heuristic for the vehicle routing problem with time windows and split deliveries

Abstract The routing of a fleet of vehicles to service a set of customers is important in the field of distribution. Vehicle routing problems (VRP) arise in many real-life applications within transportation and logistics. In this paper, we study a variant of the general VRP, VRP with time windows and split deliveries (VRPTWSD). Time constrained routing is relevant for applications where a schedule has to be followed. The option of splitting a demand makes it possible to service a customer whose demand exceeds the vehicle capacity. Splitting also allows to decrease costs. Although VRPTWSD is a relaxation of the VRP with time windows, the problem does not become easier to solve, and is still NP-hard. In this work, we propose a solution method based on tabu search for solving the VRPTWSD without imposing any restrictions on the split delivery options. We also give an analysis of experimental results on problems with 100 customers.

Path relinking for the vehicle routing problem

This paper describes a tabu search heuristic with path relinking for the vehicle routing problem. Tabu search is a local search method that explores the solution space more thoroughly than other local search based methods by overcoming local optima. Path relinking is a method to integrate intensification and diversification in the search. It explores paths that connect previously found elite solutions. Computational results show that tabu search with path relinking is superior to pure tabu search on the vehicle routing problem.

Designing delivery districts for the vehicle routing problem with stochastic demands

This paper considers the problem of designing districts for vehicle routing problems with stochastic demands. In particular, demands are assumed to be uncertain at the time when the districts are made, and these are revealed only after the districting decisions are determined. Tabu search and multistart heuristics for this stochastic districting problem are developed and compared. Computational results show that tabu search is superior over multistart.

The use of meta-heuristics for airport gate assignment

Improper assignment of gates may result in flight delays, inefficient use of the resource, customers dissatisfaction. A typical metropolitan airport handles hundreds of flights a day. Solving the gate assignment problem (GAP) to optimality is often impractical. Meta-heuristics have recently been proposed to generate good solutions within a reasonable timeframe. In this work, we attempt to assess the performance of three meta-heuristics, namely, genetic algorithm (GA), tabu search (TS), simulated annealing (SA) and a hybrid approach based on SA and TS. Flight data from Incheon International Airport are collected to carry out the computational comparison. Although the literature has documented these algorithms, this work may be a first attempt to evaluate their performance using a set of realistic flight data.

Solving a manpower scheduling problem for airline catering using metaheuristics

We study a manpower scheduling problem with job time windows and job-skills compatibility constraints. This problem is motivated by airline catering operations, whereby airline meals and other supplies are delivered to aircrafts on the tarmac just before the flights take-off. Jobs (flights) must be serviced within a given time-window by a team consisting of a driver and loader. Each driver/loader has the skills to service some, but not all, of the airline/aircraft/configuration of the jobs. Given the jobs to be serviced and the roster of workers for each shift, the problem is to form teams and assign teams and start-times for the jobs, so as to service as many flights as possible. Only teams with the appropriate skills can be assigned to a flight. Workload balance among the teams is also a consideration. We present model formulations and investigate a tabu search heuristic and a simulated annealing heuristic approach to solve the problem. Computational experiments show that the tabu search approach outperforms the simulated annealing approach, and is capable of finding good solutions.

Local search heuristics for the probabilistic dial-a-ride problem

This paper introduces the probabilistic dial-a-ride problem, and describes an efficient request-relocation neighborhood evaluation procedure for the problem. The running time of the procedure is

GRASP with path relinking for the selective pickup and delivery problem

{\mathcal{O}(n^5)}

Hybrid tabu searches for effective airport gate management

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