Facilitating sustainable development in Chile: a survey of suitable energy technologies
In: International journal of sustainable development & world ecology, Band 16, Heft 5, S. 322-331
ISSN: 1745-2627
7 Ergebnisse
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In: International journal of sustainable development & world ecology, Band 16, Heft 5, S. 322-331
ISSN: 1745-2627
In: International journal of sustainable development & world ecology, Band 19, Heft 4, S. 311-320
ISSN: 1745-2627
In: International Journal of Sustainable Society, Band 3, Heft 3, S. 225
ISSN: 1756-2546
In: Climate policy, Band 4, Heft 1, S. 45-63
ISSN: 1752-7457
In: International journal of sustainable development & world ecology, Band 20, Heft 1, S. 1-8
ISSN: 1745-2627
In: International journal of decision sciences, risk and management: IJDSRM, Band 1, Heft 1/2, S. 36
ISSN: 1753-7177
In: Business process management journal, Band 9, Heft 2, S. 221-247
ISSN: 1758-4116
In the current competitive environment, each company faces a number of challenges: quick response to customers' demands, high quality of products or services, customers' satisfaction, reliable delivery dates, high efficiency, and others. As a result, during the last five years many firms have proceeded to the adoption of enterprise resource planning (ERP) solutions. ERP is a packaged software system, which enables the integration of operations, business processes and functions, through common data‐processing and communications protocols. However, the majority, if not all, of these systems do not support the production scheduling process that is of crucial importance in today's manufacturing and service industries. In this paper, the authors propose a knowledge‐based system for production‐scheduling that could be incorporated as a custom module in an ERP system. This system uses the prevailing conditions in the industrial environment in order to select dynamically and propose the most appropriate scheduling algorithm from a library of many candidate algorithms.