this paper studies the hybrid flow shop scheduling where the optimization criterion is the minimization of total tardiness. first, the problem is formulated as a mixed integer linear programming model. then, to solve large problem sizes, an artificial immune algorithm hybridized with a simple local search in form of simulated annealing is proposed. two experiments are carried out to evaluate th...

Multi-objective integer or mixed-integer programming problems typically have disconnected feasible domains, making the task of constructing an approximation Pareto front challenging. The present article shows that certain algorithms were originally devised for continuous can be successfully adapted to approximate integer, and mixed-integer, multi-objective problems. Relationships amongst variou...

In this paper, power distribution planning (PDP) considering distributed generators (DGs) is investigated as a dynamic multi-objective optimization problem. Moreover, Monte Carlo simulation (MCS) is applied to handle the uncertainty in electricity price and load demand. In the proposed model, investment and operation costs, losses and purchased power from the main grid are incorporated in the f...

In this paper we consider multistage stochastic programs with endogenous parameters where investment strategies are considered to reduce uncertainty, and time-varying distributions are used to describe uncertainty. We present the proposed ideas in the context of the planning of process networks with uncertain yields. We propose a new mixed-integer/disjunctive programming model which is reformul...

We consider the planning and scheduling of production in a multitask/multistage batch manufacturing process typical of industries such as chemical manufacturing, food processing, and oil refining. We allow instances in which multiple sequences of tasks may be used to produce end products. We formulate the problem as a mixed-integer linear program and show that the linear programming relaxation ...

We consider the planning and scheduling of production in a multi-task/multi-stage batch manufacturing process typical of industries such as chemical manufacturing, food processing, and oil refining. We allow instances in which multiple sequences of tasks may be used to produce end products. We formulate the problem as a mixed integer linear program and show that the linear programming relaxatio...

Process planning and production scheduling play important roles in manufacturing systems. In this paper a multiobjective mixed integer linear programming model is presented for the integrated planning and scheduling of multi-product. The aim is to find a set of high-quality trade-off solutions. This is a combinatorial optimization problem with substantially large solution space, suggesting that...

In the recent decade, special attention is paid to reverse logistic due to economic benefits of recovery and recycling of used products as well as environmental legislation and social concerns. On the other hand، many researches claim that separately and sequential planning of forward and reverse logistic causes sub-optimality. Effective transport activities are also one of the most important c...

This paper aims to investigate the integrated production/distribution and inventory planning for perishable products with fixed life time in the constant condition of storage throughout a two-echelon supply chain by integrating producers and distributors. This problem arises from real environment in which multi-plant with multi-function lines produce multi-perishable products with fixed life ti...

Operator-counting is a recently developed framework for analysing and integrating many state-ofthe-art heuristics for planning using Linear Programming. In cost-optimal planning only the objective value of these heuristics is traditionally used to guide the search. However the primal solution, i.e. the operator counts, contains useful information. We exploit this information using a SATbased ap...