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InterCriteria Analyzis of Hybrid Ant Colony Optimization Algorithm for Multiple Knapsack Problem

Fidanova Stefka, Ganzha Maria, Roeva Olympia

Annals of Computer Science and Information Systems

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2021

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Vol. 25

173--180

EN

The local search procedure is a method for hybridization and improvement of the main algorithm, when complex problems are solved. It helps to avoid local optimums and to find faster the global one. In this paper we apply InterCriteria analysis (ICrA) on hybrid Ant Colony Optimization (ACO) algorithm for Multiple Knapsack Problem (MKP). The aim is to study the algorithm behavior comparing with traditional ACO algorithm. Based on the obtained numerical results and on the ICrA approach the efficiency and effectiveness of the proposed local search procedure are confirmed.

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Optimal vehicle route schedules in picking up and delivering cargo containers considering time windows in logistics distribution networks: A case study

Le Thi Diem Chau, Nguyen Duy Duc, Oláh Judit, Pakurár Miklós

Production Engineering Archives

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2020

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Vol. 26, Iss. 4

174--184

EN

This study describes a pickup and delivery vehicle routing problem, considering time windows in reality. The problem of tractor truck routes is formulated by a mixed integer programming model. Besides this, three algorithms - a guided local search, a tabu search, and simulated annealing - are proposed as solutions. The aims of our study are to optimize the number of internal tractor trucks used, and create optimal routes in order to minimize total logistics costs, including the fixed and variable costs of an internal vehicle group and the renting cost of external vehicles. Besides, our study also evaluates both the quality of solutions and the time to find optimal solutions to select the best suitable algorithm for the real problem mentioned above. A novel mathematical model is formulated by OR tools for Python. Compared to the current solution, our results reduced total costs by 18%, increased the proportion of orders completed by internal vehicles (84%), and the proportion of orders delivered on time (100%). Our study provides a mathematical model with time constraints and large job volumes for a complex distribution network in reality. The proposed mathematical model provides effective solutions for making decisions at logistics companies. Furthermore, our study emphasizes that simulated annealing is a more suitable algorithm than the two others for this vehicle routing problem.

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Iterated Local Search for Foundry Lot-sizing and Scheduling Problem with Setup Costs

Stawowy A., Duda J.

Archives of Foundry Engineering

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2017

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Vol. 17, iss. 4

161--164

EN

The paper presents a novel Iterated Local Search (ILS) algorithm to solve multi-item multi-family capacitated lot-sizing problem with setup costs independent of the family sequence. The model has a direct application to real production planning in foundry industry, where the goal is to create the batches of manufactured castings and the sequence of the melted metal loads to prevent delays in delivery of goods to clients. We extended existing models by introducing minimal utilization of furnace capacity during preparing melted alloy. We developed simple and fast ILS algorithm with problem-specific operators that are responsible for the local search procedure. The computational experiments on ten instances of the problem showed that the presence of minimum furnace utilization constraint has great impact on economic and technological conditions of castings production. For all test instances the proposed heuristic is able to provide the results that are comparable to state-of-the art commercial solver.