Abstract-This paper addresses the deadlock (DL)-free scheduling problem of flexible manufacturing systems (FMS) characterized by resource sharing, limited buffer capacity, routing flexibility, and the availability of material handling systems. The FMS scheduling problem is formulated using timed colored Petri net (TCPN) modeling where each operation has a certain number of preconditions, an estimated duration, and a set of postconditions. Based on the reachability analysis of TCPN modeling, we propose a new anytime heuristic search algorithm which finds optimal or near-optimal DL-free schedules with respect to makespan as the performance criterion. The methodology tackles the time-constrained problem of very demanding systems (high diversity production and make-to-order) in which computational time is a critical factor to produce optimal schedules that are DL-free. In such a rapidly changing environment and under tight customer due-dates, producing optimal schedules becomes intractable given the time limitations and the NP-hard nature of scheduling problems. The proposed anytime search algorithm combines breadth-first iterative deepening A * with suboptimal breadth-first heuristic search and backtracking. It guarantees that the search produces the best solution obtained so far within the allotted computation time and provides better solutions when given more time. The effectiveness of the approach is evaluated on a comprehensive benchmark set of DL-prone FMS examples and the computational results show the superiority of the proposed approach over the previous works.Index Terms-Anytime heuristic search, deadlock-free, flexible manufacturing systems (FMS), Petri nets (PN), reachability analysis, scheduling.
To achieve a significant improvement in the overall performance of a flexible manufacturing system, the scheduling process must consider the interdependencies that exist between the machining and transport systems. However, most works have addressed the scheduling problem as two independent decision making problems, assuming sufficient capacity in the transport system. In this paper, we study the simultaneous scheduling (SS) problem of machines and automated guided vehicles using a timed coloured Petri net (TCPN) approach under two performance objectives; makespan and exit time of the last job. The modelling approach allows the evaluation of all the feasible vehicle assignments as opposed to the traditional dispatching rules and demonstrates the benefits of vehicle-controlled assignments over machine-controlled for certain production scenarios. In contrast with the hierarchical decomposition technique of existing approaches, TCPN is capable of describing the dynamics and evaluating the performance of the SS problem in a single model. Based on TCPN modelling, SS is performed using a hybrid heuristic search algorithm to find optimal or near-optimal schedules by searching through the reachability graph of the TCPN with heuristic functions. Large-sized instances are solved in relatively short computation times, which were a priori unsolvable with conventional search algorithms. The algorithm's performance is evaluated on a benchmark of 82 test problems. Experimental results indicate that the proposed algorithm performs better than the conventional ones and compares favourably with other approaches.
Given the fluctuations in demand, diversity in products, production flexibility requirements, and tight customer due dates, obtaining optimal production schedules is considered a complex research problem. This can drastically affect the survival of some manufacturing companies in today's fiercely competitive global market. In a very demanding decision-making environment, scheduling problems are dealt with in a short-term horizon, in which computation time is a critical factor. Producing optimal solutions is practically impossible given the time limitations and the nondeterministic polynomial (NP)-hard nature of scheduling problems. This paper presents an anytime-heuristic search approach based on a simulation-optimization framework that combines evaluation methods (simulation) and search methods (optimization) through the reachability analysis (or state space) of timed colored Petri net models to schedule flexible manufacturing systems (FMS). The anytime search algorithm is capable of finding a first suboptimal solution very quickly and continuously improves the solution quality over time. If given enough computation time, the algorithm eventually converges to an optimal solution. The proposed approach is aimed at obtaining optimal or near-optimal solutions to FMS scheduling problems in relatively short computation times with the objective of minimizing the makespan. Its effectiveness is highlighted with excellent results that outperform previous methods on benchmark examples with flexible material handling systems, machine, and routing configurations. The approach can also serve as a decision support tool to assist production schedulers that require rapid and almost real-time responses to time-critical production scheduling on the shop floor.
Women are increasingly being recognised as equal partners in development. However, there is a growing awareness that negative health, social and economic consequences act as barriers in their efforts to contribute to sustainable development. Consequently, to fully harness the potentials of women in this regard, these barriers have to be addressed. This paper utilises qualitative data collected as part of an intervention programme designed to increase access to reproductive health information/services and economic resources among young women in Osogbo, Nigeria. The aim was to provide reproductive health information and training in basic business skills and micro-credit facilities to enable beneficiaries to establish private businesses. Findings from the study highlight the importance of the relationship between female education, access to economic resources as a means of furthering empowerment of women especially in terms of their reproductive behaviour. The paper argues that increased access to resources is a major factor toward ensuring the much desired empowerment.
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