Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
Heuristics for the traveling salesman problem with pickup and delivery
Computers and Operations Research
Intensification and diversification with elite tabu search solutions for the linear ordering problem
Computers and Operations Research
Scatter search for the linear ordering problem
New ideas in optimization
An Experimental Evaluation of a Scatter Search for the Linear Ordering Problem
Journal of Global Optimization
A novel metaheuristics approach for continuous global optimization
Journal of Global Optimization
A tabu scatter search metaheuristic for the arc routing problem
Computers and Industrial Engineering - Special issue: Focussed issue on applied meta-heuristics
A Template for Scatter Search and Path Relinking
AE '97 Selected Papers from the Third European Conference on Artificial Evolution
BDD Variable Ordering by Scatter Search
ICCD '01 Proceedings of the International Conference on Computer Design: VLSI in Computers & Processors
Advances in evolutionary computing
DNA Sequencing--Tabu and Scatter Search Combined
INFORMS Journal on Computing
Journal of Global Optimization
Computers and Operations Research
A scatter search algorithm for project scheduling under partially renewable resources
Journal of Heuristics
A Comparison between Scatter Search and the RAND Method for Solving the Joint Replenishment Problem
MICAI '06 Proceedings of the Fifth Mexican International Conference on Artificial Intelligence
A multi-objective scatter search for a mixed-model assembly line sequencing problem
Advanced Engineering Informatics
A scatter search-based heuristic to locate capacitated transshipment points
Computers and Operations Research
SSPMO: A Scatter Tabu Search Procedure for Non-Linear Multiobjective Optimization
INFORMS Journal on Computing
Context-Independent Scatter and Tabu Search for Permutation Problems
INFORMS Journal on Computing
On optimal cell assignments in PCS networks
PCC '02 Proceedings of the Performance, Computing, and Communications Conference, 2002. on 21st IEEE International
A particle swarm optimization for the vehicle routing problem with simultaneous pickup and delivery
Computers and Operations Research
Expert Systems with Applications: An International Journal
An ant colony system (ACS) for vehicle routing problem with simultaneous delivery and pickup
Computers and Operations Research
A scatter search approach to the optimum disassembly sequence problem
Computers and Operations Research
A parallel heuristic for the Vehicle Routing Problem with Simultaneous Pickup and Delivery
Computers and Operations Research
Expert Systems with Applications: An International Journal
A multi-objective particle swarm optimizer hybridized with scatter search
MICAI'06 Proceedings of the 5th Mexican international conference on Artificial Intelligence
New ideas in applying scatter search to multiobjective optimization
EMO'05 Proceedings of the Third international conference on Evolutionary Multi-Criterion Optimization
BDD minimization by scatter search
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
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In parallel with the growth of both domestic and international economies, there have been substantial efforts in making manufacturing and service industries more environmental friendly (i.e., promotion of environmental protection). Today manufacturers have become much more concerned with coordinating the operations of manufacturing (for new products) and recycling (for reuse of resources) together with scheduling the forward/reverse flows of goods over a supply chain network. The stochastic travel-time vehicle routing problem with simultaneous pick-ups and deliveries (STT-VRPSPD) is one of the major operations problems in bi-directional supply chain research. The STT-VRPSPD is a very challenging and difficult combinatorial optimization problem due to many reasons such as a non-monotonic increase or decrease of vehicle capacity and the stochasticity of travel times. In this paper, we develop a new scatter search (SS) approach for the STT-VRPSPD by incorporating a new chance-constrained programming method. A generic genetic algorithm (GA) approach for STT-VRPSPD is also developed and used as a reference for performance comparison. The Dethloff data will be used to evaluate the performance characteristics of both SS and GA approaches. The computational results suggest that the SS solutions are superior to the GA solutions.