Part I Intractable combinatorial optimization problems. PSC-algorithms -- Optimal scheduling for two criteria for a single machine with arbitrary due dates -- Optimal tasks execution for two criteria with a common due date on parallel machines -- Optimal scheduling for the vector criterion for parallel machines with arbitrary due dates -- The total weighted tardiness of tasks minimization on a single machine -- The total earliness/tardiness minimization on a single machine with arbitrary due dates -- The total tardiness of tasks minimization on identical parallel machines with a common due date -- Minimization of the maximum earliness/tardiness of tasks on identical parallel machines with a common due date -- The total weighted completion time of tasks minimization with precedence relations on a single machine -- Part II: Hierarchical planning and decision making in network systems with limited resources -- The four-level model of planning and decision making -- Algorithmic support of the four-level model of planning and decision making -- Models and methods of decision making with non-formalized goals -- Project 1. Informational Decision Support System for the project management in software development -- Project 2. Universal hierarchical system of scheduling and operational planning for the small-scale type of productions.

The book focuses on the next fields of computer science: combinatorial optimization, scheduling theory, decision theory, and computer-aided production management systems. It also offers a quick introduction into the theory of PSC-algorithms, which are a new class of efficient methods for intractable problems of combinatorial optimization. A PSC-algorithm is an algorithm which includes: sufficient conditions of a feasible solution optimality for which their checking can be implemented only at the stage of a feasible solution construction, and this construction is carried out by a polynomial algorithm (the first polynomial component of the PSC-algorithm); an approximation algorithm with polynomial complexity (the second polynomial component of the PSC-algorithm); also, for NP-hard combinatorial optimization problems, an exact subalgorithm if sufficient conditions were found, fulfilment of which during the algorithm execution turns it into a polynomial complexity algorithm. Practitioners and software developers will find the book useful for implementing advanced methods of production organization in the fields of planning (including operative planning) and decision making. Scientists, graduate and master students, or system engineers who are interested in problems of combinatorial optimization, decision making with poorly formalized overall goals, or a multiple regression construction will benefit from this book.