Contributed Session Wed.3.H 3012

Wednesday, 15:15 - 16:45 h, Room: H 3012

Cluster 2: Combinatorial optimization [...]

Heuristics III

 

Chair: Beyzanur Cayir

 

 

Wednesday, 15:15 - 15:40 h, Room: H 3012, Talk 1

Polina Kononova
Local search heuristic for the buffer-constrained two-stage multimedia scheduling problem

Coauthor: Yury Kochetov

 

Abstract:
We consider a two-machine flowshop scheduling problem originating in the multimedia industry. It is known that the problem is strongly NP-hard. We present some ILP-reformulations to get lower bounds and VNS-metaheuristic to find optimal or near optimal solutions. The Kernighan-Lin neighborhoods and job-window neighborhoods are used in the VNS framework. For experiments we generate large scale instances with known global optima. Computational results and some open questions are discussed.

 

 

Wednesday, 15:45 - 16:10 h, Room: H 3012, Talk 2

Beyzanur Cayir
A genetic algorithm for truck to door assignment in warehouses

Coauthor: Nil Aras

 

Abstract:
Customer satisfaction is crucial for companies to survive. Right shipment planning is indispensible process of warehouse management in supply chain and logistics management. This problem is similar to the problem of gate assignments in airports. We consider the over-constrained truck-to-door assignment problem with time window, operational time and customer priority constraints in warehouse where the number of vehicles exceed the number of doors available. The problem feasibility is affected by three factors: the arrival and departure time window of each type of vehicle, loading time for orders, total distance to customers. Objective of this study is to minimize total lead time and deviations from expected delivery time. Otherwise a penalty cost occurs for late or early delivery. Penalty cost depends on customer priorities. In this study, formulation of a mixed integer model for optimal solution of the vehicle scheduling problem is described and a genetic algorithm is proposed which can search for practical optimal solutions, on the basis of the theory of natural selection, without performing all searches. The computational experiment is carried out on real life instances.

 

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