MemeticAlgorithmand Genetic Algorithm for the Single Machine Scheduling Problem with Linear Earliness and Quadratic Tardiness Costs
نویسنده
چکیده
The Single Machine Scheduling (SMS) problem with Multiple Objective Function (MOF) is one of the most representative problems in the scheduling area. In this paper, we consider the SMS problem with linear earliness and quadratic tardiness costs, and no machine idle time. The chosen method is based on memetic algorithm and genetic algorithm. For this purpose, Genetic Algorithms (GA) are a population-based Meta heuristics. They have been successfully applied to many optimization problems. A Memetic Algorithm (MA) is an extension of the traditional genetic algorithm. And we introduce two types of crossover. The methods were tested and various experimental results show that MA performs better than the GA for big jobs but GA was better with small jobs. صلختسملا تنأسم ( ةِذيحىنا تِىكامنا تنوذج SMS ) هم ةذحاو فاذهلأا ةدذعتم تناد عم شثكأ تيجرىمىنا مئاسمنا يف ِقاطو يف .تنوذجنا يزه ثحبنا شُبتعَو ، تنأسم لاو ،تِيواثنا تجسذنا هم شِخأتنا فِهكو ِّ يطخنا شِيكبتناب ةِذيحىنا تِىكامنا تنوذج ندىجو فلىت َةشتف ىهع .تيثاسو تيمصساىخو كيتيميم تِيمصساىخ ىهع ةذىتسم َةسَاَتخمُنا َتميشطنا نّإ .تِىكام تيثاسو ثايمصساىخ ،ضِشغنا ازهن (GA) بيمىتنا دذعتم عمتجم ةذعال عم . هحو مذُّل ى هْمِ ذيذعنا ىنإ ا مئاسم تيهثملأا كِيمحت ( كيتيميم تيمصساىخ .حاجىب MA ) داذتما .تِيذيهمتنا تِيثاسىنا تِيمصساىخن كنزك ِلامتولااعِاىوأىْمِواىثئمُذّمُو . َتفِهَتخْمُوَتبشّجمَُتيبيشجتجَِئاتَىتْواكَلشطنا هيبت ّنأب MA ْهمِهضفأيدّؤُي GA لأن لامع هكنةِشيبكنا GA لأابَهضفأتْواكَ لامع ِةشيغصنا .
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