scholarly journals NSGAII enhanced with a local search for the vehicle routing problem with time windows and synchronization constraints

2016 ◽  
Vol 49 (12) ◽  
pp. 1198-1203 ◽  
Author(s):  
S.R. Ait Haddadene ◽  
N. Labadie ◽  
C. Prodhon
1998 ◽  
Vol 1617 (1) ◽  
pp. 171-178 ◽  
Author(s):  
How-Ming Shieh ◽  
Ming-Der May

The problem of the on-line version of the vehicle routing problem with time windows (VRPTW) differs from the traditional off-line problem in the dynamical arrival of requests and the execution of the partial tour during the run time. The study develops an on-line optimization-based heuristic that combined the concepts of the “on-line algorithm,” “anytime algorithm,” and local search heuristics to solve the on-line version of VRPTW. The solution heuristic is evaluated with modified Solomon’s problems. By comparing with these benchmark problems, the different results between on-line and off-line algorithms are indicated.


Author(s):  
Alexander Jungwirth ◽  
Guy Desaulniers ◽  
Markus Frey ◽  
Rainer Kolisch

We study a new variant of the vehicle routing problem, which arises in hospital-wide scheduling of physical therapists. Multiple service locations exist for patients, and resource synchronization for the location capacities is required as only a limited number of patients can be treated at one location at a time. Additionally, operations synchronization between treatments is required as precedence relations exist. We develop an innovative exact branch-price-and-cut algorithm including two approaches targeting the synchronization constraints (1) based on branching on time windows and (2) based on adding combinatorial Benders cuts. We optimally solve realistic hospital instances with up to 120 treatments and find that branching on time windows performs better than adding cutting planes. Summary of Contribution: We present an exact branch-price-and-cut (BPC) algorithm for the therapist scheduling and routing problem (ThSRP), a daily planning problem arising at almost every hospital. The difficulty of this problem stems from its inherent structure that features routing and scheduling while considering multiple possible service locations with time-dependent location capacities. We model the ThSRP as a vehicle routing problem with time windows and flexible delivery locations and synchronization constraints, which are properties relevant to other vehicle routing problem variants as well. In our computational study, we show that the proposed exact BPC algorithm is capable of solving realistic hospital instances and can, thus, be used by hospital planners to derive better schedules with less manual work. Moreover, we show that time window branching can be a valid alternative to cutting planes when addressing synchronization constraints in a BPC algorithm.


2003 ◽  
Vol 12 (02) ◽  
pp. 153-172 ◽  
Author(s):  
Olli Bräysy ◽  
Wout Dullaert

This paper presents a new evolutionary metaheuristic for the vehicle routing problem with time windows. Ideas on multi-start local search, ejection chains, simulated annealing and evolutionary computation are combined in a heuristic that is both robust and efficient. The proposed method produces results that are on par with the current best solutions, at a fraction of the computation time needed by previous best approaches. Given the significantly lower time consumption over methods proposed previously in the literature, we consider our approach especially useful in dynamic routing problems, where decisions must be made in real-time.


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