A novel solution approach for solving travelling salesman problem based on Hungarian algorithm

Bu çalışmada kombinatoryal optimizasyon alanının ünlü problemlerinden olan gezgin satıcı ve atama problemleri arasındaki ilişkiden faydalanan yeni bir çözüm algoritması önerilmektedir. Atama problemleri için optimal çözümü veren Macar Algoritması ile simetrik gezgin satıcı problemi için başlangıç çözümleri elde edilmiştir. Elde edilen başlangıç çözümleri En Yakın Komşu ve 2-Opt (NNH_2-Opt) sezgiselleri kullanılarak çözülmüştür. Önerilen yaklaşım sıklıkla kullanılan gezgin satıcı test problemleri ile analiz edilmiş ve bilimsel yazında yer alan bazı çalışmaların sonuçları ile kıyaslama yapılmıştır. Sonuç olarak, önerilen yöntemin hem çözüm hızı hem de çözüm kalitesi bakımından kıyaslanan yöntemlere göre iyi olduğu gösterilmiştir. Özellikle, problem boyutu büyüdükçe kıyaslanan yöntemlerin çözüm süresi uzarken, önerilen yöntem büyük boyutlu problemler için de hızlı çözümler sunabilmektedir

Simulation as a Method of Choosing the Order Picking Concept

The analysis of the three, main, heuristics approaches outlining the order picking routes in a warehouse, is a subject of this paper. Order picking is the most laborious warehouse process and it contributes to 55% - 65% of all the costs of operations performed in a warehouse. The most time consuming order picking activity, according to the research, is transfer which is closely related to, adopted by a given company, system of transfer and movement between the points of taking the order, places of pick up, and points of release. Even the small shifts of commodities, on short distances, play a very important part in modern dynamic economy. On the basis of a simple model of a warehouse owned by an authentic company, a computer program was created, which helps in simulation of the three, main heuristics approaches to outline the routes, so as to make the order picking process as short as possible

Forklift Routing in Warehouses Using Dual-Commands and Stackable Pallets

This research determines time optimal routes for loading and picking pallets that can be stacked on top of each other during transport in a manual warehouse that only contains full pallets and utilizes single deep storage. This research was motivated by the fact that we are seeing this situation on an ever increasing basis, particularly in warehouses that supply parts to automotive assembly. In practice, forklift drivers have developed strategies to take advantage of this opportunity but to our knowledge there is no literature that addresses this problem rigorously. The important features of this work are that a time based mathematical model is required because the time spent stacking and unstacking pallets can be significant and a modeling approach to including stacking had to be developed. The basic models are included here with examples and insights into future work required for applicability to a wider range of users

Exact algorithms for the order picking problem

Order picking is the problem of collecting a set of products in a warehouse in a minimum amount of time. It is currently a major bottleneck in supply-chain because of its cost in time and labor force. This article presents two exact and effective algorithms for this problem. Firstly, a sparse formulation in mixed-integer programming is strengthened by preprocessing and valid inequalities. Secondly, a dynamic programming approach generalizing known algorithms for two or three cross-aisles is proposed and evaluated experimentally. Performances of these algorithms are reported and compared with the Traveling Salesman Problem (TSP) solver Concorde

Reducing blocking effects in multi-block layouts

Tour planning in multi-block layouts is a common exercise in logistics. In those systems, blocking effects result from conflicting agents competing for resources. Although clearly exceptional in real world applications, most methods of tour planning assume only one active agent, and thus do not consider blocking effects. In this paper we examine heuristic methods of tour planning in multi-block layouts with multiple agents, finding that blocking effects have a significant impact on system performance. We show that methods devised for the mentioned special case do not scale very well when applied to scenarios with multiple agents. We propose a heuristic method which is capable of reducing blocking effects. It generates tours of equal or shorter length than those produced by the other examined methods

Reducing blocking effects in multi-block layouts

Tour planning in multi-block layouts is a common exercise in logistics. In those systems, blocking effects result from conflicting agents competing for resources. Although clearly exceptional in real world applications, most methods of tour planning assume only one active agent, and thus do not consider blocking effects. In this paper we examine heuristic methods of tour planning in multi-block layouts with multiple agents, finding that blocking effects have a significant impact on system performance. We show that methods devised for the mentioned special case do not scale very well when applied to scenarios with multiple agents. We propose a heuristic method which is capable of reducing blocking effects. It generates tours of equal or shorter length than those produced by the other examined methods