30 Journal on Processing and Energy in Agriculture 18 (2014) 1 Biblid: 1821-4487 (2014) 18; 1; p 30-35 Original Scientific Paper UDK: 626.4 Originalni naučni rad OPTIMIZATION OF SHIP LOCK CONTROL SYSTEM USING SWARM-BASED TECHNIQUES OPTIMIZACIJA RADA BRODSKE PREVODNICE UPOTREBOM TEHNIKA BAZIRANIH NA IMITACIJI PONAŠANJA ROJEVA Željko KANOVIĆ, Vladimir BUGARSKI, Todor BAČKALIĆ, Zoran JELIČIĆ, Milena PETKOVIĆ, Dragan MATIĆ University of Novi Sad, Faculty of Technical Sciences,21000 Novi Sad, Trg Dositeja Obradovića 6, Serbia e-mail:kanovic@uns.ac.rs ABSTRACT This paper presents the application of some well-known global optimization techniques in optimization of an expert system con- trolling a ship locking process. Optimization was conducted in order to achieve better results in local distribution of ship arrivals, i.e. lower waiting times for ships and less empty lockages. Particle swarm optimization, artificial bee colony optimization and genetic algorithm were used. The results shown in this paper confirmed that all these procedures show similar results and provide overall improvement of ship lock operation performance, which speaks in favor of their application in similar transportation problem optimi- zation. Key words: Ship lock, fuzzy expert system, particle swarm optimization, artificial bee colony optimization, genetic algorithm. REZIME U ovom radu prikazana je upotreba globalnih optimizacionih metoda cilju optimizacije ekspertskog sistema za upravljanje brods- kom prevodnicom. Optimizacija je sprovedena radi poboljšanja performansi sistema, odnosno skraćivanja vremena čekanja brodova i smanjenja broja prevođenja na prazno. Upotrebljeni su algoritam optimizacije rojem čestica, veštačka kolonija pčela i genetski al- goritam. Prikazani rezultati potvrđuju da svi ovi postupci postižu slične rezultate, poboljšavajući performanse rada brodske prevod- nice i da ih je moguće uspešno primeniti u ovakvim i sličnim problemima optimizacije transporta. Ključne reči: Brodska prevodnica, ekspertski fazi sistemi, optimizacija rojem čestica, veštačka kolonija pčela, genetski algoritam. INTRODUCTION Ship locks are designed to enable ships to overcome rises in the water level and help to maintain navigation on inland water- ways (Partenscky, 1986). A ship lock or navigation lock is a hy- draulic structure that consists of an enclosed chamber with wa- tertight gates at each end. The water level difference is sur- mounted by filling or emptying the lock chamber. By raising or lowering the level of a body of water, the vessel itself goes up or down accordingly. The ship lock operators or lock masters al- ways attempt to fill or empty the lock in the fastest time possible with a minimum of turbulence. The organization of vessel traffic on a waterway in the zone of a ship lock is a compromise be- tween rational utilization of the lock and minimizing of ship’s delay while waiting to transit the lock (Bačkalić, 2000; Smith et al, 2009). The basic elements of a classic ship lock are presented in (Bačkalić, 2000; Bugarski et al, 2013). This paper presents the performance optimization of Fuzzy Expert System (FES) designed to assist the ship lock operators in the decision-making process. From a wide range of types of ship locks the choice was narrowed to a system that is usually applied on navigable channels on inland waterways: single- channel queuing system with two independent, stochastic streams of arrivals from two opposite directions. Although the model has been established and tested in a particular real system, the principle of generality is not lost. With minor changes in the design of FES, the proposed model can be extended to any other lock from the observed category. Campbell (Campbell et al, 2007) presented the decision tools for reducing congestion at locks on the upper Mississippi river. Bugarski, Bačkalić and Kuzmanov (Bugarski et al, 2013) pro- posed a fuzzy decision support system for controlling a ship lock. Fuzzy logic is chosen as a control method that does not re- quire a precise mathematical model of the controlled system (Kecman, 2001) and as the most suitable mathematical approach for addressing uncertainty, subjectivity, polysemy and indefi- niteness (Kosko, 1993). Teodorović and Vukadinović (Teodorović and Vukadinović, 1998) successfully applied fuzzy logic and artificial intelligence in traffic control. The main objective of this study is to optimize the perfor- mance of fuzzy expert system controlling the ship lock, in order to achieve the best value of the economic criterion defined as a linear combination of two opposite criteria. The first one is a minimum number of empty lockages (lockages without a ves- sel), and the second one is minimal waiting time (ship’s delay). Fuzzy system is a complicated decision system, described by highly non-linear and logic functions, and it is very difficult to obtain a model of such a system described by analytical expres- sions. Thus, it is chosen to apply global numerical optimization algorithms, which provide thorough investigation of the search space and, in this particular case, a more reliable solution than some classic analytical approaches. Three popular global optimi- zation algorithms were used: Particle Swarm Optimization (PSO), Artificial Bee Colony Optimization (ABC) and Genetic Algorithm (GA), with objective to find the best optimization technique for the presented expert system controlling a ship lock process. All these algorithms have been frequently used in engi- neering applications (Teodorović and Dell’Orco, 2005; Kanović et al, 2011). The results obtained in this research proved that it is possible to design an optimal FES enabling control over eco- nomic performance of the entire system, and also that global op- timization algorithms used in the study can be successfully ap- plied in problems concerning transportation performance im- provement and optimization. MATERIAL AND METHOD The ship lock “Kucura” (Fig. 1) on the Danube-Tisa-Danube hydro system in Serbia was observed as a representative real sys-