www.tjprc.org SCOPUS Indexed Journal editor@tjprc.org SINGLE OBJECTIVE FOR AN INTEGER PARTIAL FLEXIBLE OPEN SHOP SCHEDULING PROBLEM USING DEVELOPED ANT COLONY OPTIMIZATION G. UMASHANKAR 1 & D. SARAVANAN 2 1 Research Scholar of Mathematics, Bharathiyar University, Coimbatore, India 2 Professor of Mathematics, Karpavinagayakar College of Engineering, Madhuranthagam, Tamil Nadu, India ABSTRACT As an augmentation of the classical mechanical open shop scheduling problem, the Integer partial flexible open shop scheduling problem (IPFOSP) assumes an important role in genuine production systems. In IPFOSP, an operation is permitted to be prepared on in excess of one elective machine. It has been turned out to be an emphatically NP-hard problem. Ant colony optimization (ACO) has been turned out to be a successful approach for managing IFOSP. Since, the key ACO has two essential bothers including low computational efficiency and local ideal. In defect these two brothers, a developed ant colony optimization (DACO) is proposed to propel the make span for IPFOSP. The accompanying perspectives are done on our developed ant colony optimization algorithm: select machine govern problems, instate uniform appropriated mechanism for ants, change pheromone’s coordinating mechanism, select hub method, and refresh pheromone’s mechanism. The genuine production instance and two plans of well –known benchmark instances are inspected and correlations with some unique approaches conform the viability of the proposed DACO. The results reveal that our proposed DACO can give better arrangement in a sensitive computational time. KEYWORDS:- DACO, IPFOSP & Ant colony optimization (ACO) Received: Apr 08, 2018; Accepted: May 17, 2018; Published: Jun 19, 2018; Paper Id.: IJMPERDJUN2018117 INTRODUCTION Scheduling problem assumes an essential part in numerous industrial systems [1]. In this best approach it has amazing considerable researches for late decades [2–7]. Open shop scheduling problem (OSP) is a branch of production scheduling and combinatorial optimization issues [8]. The Integer flexible open shop scheduling problem (IPFOSP) is an growth of the open shop scheduling problem (OSP) [9]. Not the same as OSP, an operation can be handled on more than one candidate machines in IPFOSP. Therefore, two sub problems facing IPFOSP are machine task and activity sequencing. Machine task is is the manner by which to dole out a machine for each activity while activity sequencing is the way to schedule all tasks on machines to optimize the given performance indicators [10]. In this way, IFPOSP is more entangled than the established OSP and it has been ended up being a firmly NP-hard in 1993 [11]. The IPFOSP was first studied by Brucker and Schliew housed a polynomial approach to deal with two opens IPFOSP [12]. In recent years, a large number of heuristics or meta-heuristics have been active to accord with IPFOSP, specifically through tabu search (TS) [13], simulated annealing (SA) [14], genetic algorithm (GA) [15, 16], particle swarm optimization (PSO) [17, 18], ant colony optimization (ACO) [19], artificial bee colony(ABC)[20], and Original Article International Journal of Mechanical and Production Engineering Research and Development (IJMPERD) ISSN(P): 2249-6890; ISSN(E): 2249-8001 Vol. 8, Issue 3, Jun 2018, 1121-1132 © TJPRC Pvt. Ltd.