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Stochastic multi-depot vehicle routing problem with pickup and delivery: an ILS approach

Rios Brenner H. O., Xavier Eduardo C., Miyazawa Flávio K., Amorim Pedro

Annals of Computer Science and Information Systems

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2020

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Vol. 21

307--315

EN

We present a natural probabilistic variation of the multi-depot vehicle routing problem with pickup and delivery (MDVRPPD). In this paper, we present a variation of this deterministic problem, where each pair of pickup and delivery points are present with some probability, and their realization are only known after the routes are computed. We denote this stochastic version by S-MDVRPPD. One route for each depot must be computed satisfying precedence constraints, where each pickup point must appear before its delivery pair in the route. The objective is to find a solution with minimum expected traveling distance. We present a closed-form expression to compute the expected length of an a priori route under general probabilistic assumptions. To solve the S-MDVRPPD we propose an Iterated Local Search (ILS) that uses the Variable Neighborhood Descent (VND) as local search procedure. The proposed heuristic was compared with a Tabu Search (TS) algorithm based on a previous work. We evaluate the performance of these heuristics on a data set adapted from TSPLIB instances. The results show that the ILS proposed is efficient and effective to solve S-MDVRPPD.

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Pick-up & Deliver in Maintenance Management of Renewable Energy Power Plants

Vincenza Carchiolo, Francesco Di Dio, Longheu Alessandro, Malgeri Michele, Mangioni Giuseppe, Romeo Antonio, Trapani Natalia

Annals of Computer Science and Information Systems

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2020

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Vol. 21

579--585

EN

Logistic optimization is a strategic element in many industrial processes, given that an optimized logistics makes the processes more efficient. A relevant case, in which the optimization of logistics can be decisive, is the maintenance in a Wind Farm where it can lead directly to a saving of energy cost. Wind farm maintenance presents, in fact, significant logistical challenges. They are usually distributed throughout the territory and also located at considerable distances from each other, they are generally found in places far from uninhabited centers and sometimes difficult to reach and finally spare parts are rarely available on the site of the plant itself. In this paper, we will study the problem concerning the optimization of maintenance logistics of wind plants based on the use of specific vehicle routing optimization algorithms. In particular a pickup-and- delivery algorithm with time-window is adopted to satisfy the maintenance requests of these plants, reducing their management costs. The solution was applied to a case study in a renewable energy power plant. Results time reduction and simplification and optimization obtained in the real case are discussed to evaluate the effectiveness and efficiency of the adopted approach.

3

Wyznaczanie i harmonogramowanie tras pojazdów przy wykorzystaniu metody BBS

Wolfenburg A.

Logistyka

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2014

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nr 4

PL

W pracy przedstawiono sposób wyznaczania i harmonogramowania tras pojazdów przy wykorzystaniu metody BBS (Branch and Bound Simulation) dla pojazdów przewożących jednocześnie ładunki pochodzące z wielu zleceń. Uwzględniono ograniczenia dotyczące ładowności pojazdów i okien czasowych w punktach załadunku i rozładunku. Opracowany algorytm wyznacza najkrótsze, najszybsze i najtańsze trasy z pewną znaną dokładnością.

EN

The work presents a method of the vehicle routing and scheduling using the Branch and Bound Simulation method for vehicles simultaneously carrying loads from multiple orders. Limitations concerning vehicle loads and time windows in points of loading and unloading are taken into consideration. The developed algorithm appoints the shortest, the fastest and the cheapest routes with a certain known accuracy.

4

Metoda wyznaczania tras jazdy pojazdów w przedsiębiorstwach komunalnych

Izdebski M., Jacyna M.

Logistyka

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2014

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nr 6

4595-4605

PL

W artykule przedstawiono metodę rozwiązującą problem wyznaczania tras jazdy pojazdów w przedsiębiorstwach komunalnych. Przedstawiona metoda składa się z trzech etapów: przygotowawczy, optymalizacyjny i generowania tras.Każdy etap została scharakteryzowana. W pracy przedstawiono model matematyczny wyznaczania tras pojazdów, określono funkcję kryterium oraz warunek wyznaczania tras załadunkowych. Minimalna trasa załadunkowa opisana w etapie optymalizacyjnym została wyznaczona algorytmem genetycznym. Opisane zostały etapy algorytmu genetycznego. Została przedstawiona struktura przetwarzana przez algorytm, funkcja przystosowania, proces krzyżowania, mutacji i inwersji. Struktura została przedstawiona jako ciąg liczb naturalnych, w procesie selekcji zastosowano metodę ruletki oraz operator krzyżowania PMX. Metodę zweryfikowano w programie C#.

EN

The paper presents a method designating the vehicle routing problem in municipal service 4605 companies.Presented method consists of three phase: the preparatory phase, the optimization phase and the generated routes phase. Each phase was characterized.In this paper the mathematical model of this problem was presented. The function of criterion and the condition on designating the routes were defined. The minimum route described in the optimization phase was designated by the genetic algorithm. In this paper the stages of constructing of the genetic algorithm were presented. A structure of the data processed by the algorithm, a function of adaptation, a selection of chromosomes, a crossover, a mutation and an inversion were characterized. A structure of the data was presented as string of natural numbers. In selection process the roulette method was used and in the crossover process the operator PMX was presented. The method was verified in programming language C #.